From 80b6a6f81bba7425b3d64f88545e6093748850d3 Mon Sep 17 00:00:00 2001
From: Logan Drescher <drescher@uchc.edu>
Date: Fri, 22 Nov 2024 17:11:36 -0500
Subject: [PATCH 1/2] Updated KiSAO OBO and added parsing for 694

---
 .../java/cbit/util/kisao/KisaoOntology.java   |    4 +-
 .../java/cbit/util/kisao/KisaoTermParser.java |   23 +-
 .../cbit/vcell/solver/SolverUtilities.java    |   56 +-
 .../java/org/vcell/sedml/SEDMLImporter.java   |    6 +-
 vcell-core/src/main/resources/kisao_algs.obo  | 6001 ++++++++++++-----
 .../kisao_algs_old_replaced_22Nov2024.obo     | 2847 ++++++++
 6 files changed, 7128 insertions(+), 1809 deletions(-)
 create mode 100644 vcell-core/src/main/resources/kisao_algs_old_replaced_22Nov2024.obo

diff --git a/vcell-core/src/main/java/cbit/util/kisao/KisaoOntology.java b/vcell-core/src/main/java/cbit/util/kisao/KisaoOntology.java
index 4a43ec2e61..c899334887 100644
--- a/vcell-core/src/main/java/cbit/util/kisao/KisaoOntology.java
+++ b/vcell-core/src/main/java/cbit/util/kisao/KisaoOntology.java
@@ -10,7 +10,7 @@
 
 public class KisaoOntology {
 	
-	private List<KisaoTerm> terms = new ArrayList<>();
+	private final List<KisaoTerm> terms = new ArrayList<>();
 	private static KisaoOntology instance;
 	
 	
@@ -61,7 +61,7 @@ public static List<KisaoTerm> makeDescendantList(KisaoTerm root) {
 			if(tmpList.size() > 1) {
 				System.err.println("Each kisao term must have no more than 1 descendant");
 			}
-			if(tmpList.size() == 0) {	// we seldom get here
+			if(tmpList.isEmpty()) {	// we seldom get here
 				if(root.getId().equals("KISAO_0000000")) {
 					throw new RuntimeException("Error reaching KISAO_0000000");
 				} else {
diff --git a/vcell-core/src/main/java/cbit/util/kisao/KisaoTermParser.java b/vcell-core/src/main/java/cbit/util/kisao/KisaoTermParser.java
index d05d18cf4a..2b9fe617da 100644
--- a/vcell-core/src/main/java/cbit/util/kisao/KisaoTermParser.java
+++ b/vcell-core/src/main/java/cbit/util/kisao/KisaoTermParser.java
@@ -6,8 +6,10 @@
 import java.io.BufferedReader;
 import java.io.InputStream;
 import java.io.InputStreamReader;
+import java.nio.file.Files;
 import java.util.regex.Matcher;
 import java.util.regex.Pattern;
+import java.util.stream.StreamSupport;
 
 
 public class KisaoTermParser {
@@ -22,16 +24,15 @@ public class KisaoTermParser {
 	final Pattern ISA_PATTERN = Pattern.compile("is_a:\\s*(\\S+)");
 	
 	KisaoOntology parse() {
-		InputStream is = KisaoTermParser.class.getClassLoader().getResourceAsStream(Kisao_OBO);
-		BufferedReader isr = new BufferedReader(new InputStreamReader(is));
-		String line = null;
-		boolean inState = false;
 		KisaoOntology ontology = new KisaoOntology();
 		KisaoTerm curr = null;
+		boolean inState = false;
+
+		InputStream is = KisaoTermParser.class.getClassLoader().getResourceAsStream(Kisao_OBO);
+        assert is != null;
 
 		try {
-			while ((line = isr.readLine()) != null) {
-				
+			for (String line : (new BufferedReader(new InputStreamReader(is))).lines().toList()){
 				if (line.matches(TERM_PATTERN)) {
 					inState = true;
 					curr = new KisaoTerm();
@@ -41,11 +42,12 @@ KisaoOntology parse() {
 					ontology.addTerm(curr);
 					curr = null;
 				}
-				
+
 				if(inState) {
 					Matcher matcher = ID_PATTERN.matcher(line);
 					if (matcher.find()) {
-						curr.setId(matcher.group(1));
+						String group1 = matcher.group(1);
+						curr.setId(group1.startsWith("kisao:") ? group1.substring(6) : group1);
 					}
 
 					matcher = NAME_PATTERN.matcher(line);
@@ -54,11 +56,12 @@ KisaoOntology parse() {
 					}
 					matcher = ISA_PATTERN.matcher(line);
 					if (matcher.find()) {
-						curr.addIsaRef(matcher.group(1));
+						String group1 = matcher.group(1);
+						curr.addIsaRef(group1.startsWith("kisao:") ? group1.substring(6) : group1);
 					}
 				}
 			}
-		} catch(Exception e) {
+		} catch (Exception e) {
 			lg.error(e.getMessage(), e);
 		}
 		
diff --git a/vcell-core/src/main/java/cbit/vcell/solver/SolverUtilities.java b/vcell-core/src/main/java/cbit/vcell/solver/SolverUtilities.java
index 6e272b1088..047f049b67 100644
--- a/vcell-core/src/main/java/cbit/vcell/solver/SolverUtilities.java
+++ b/vcell-core/src/main/java/cbit/vcell/solver/SolverUtilities.java
@@ -86,14 +86,14 @@ public static boolean isPowerOf2(int n) {
 
 	/**
 	 * Ensure solvers extracted from resources and registered as property
-	 * @param cf
+	 * @param sd the solver description
 	 * @return array of exes used by provided solver
 	 * @throws IOException, {@link UnsupportedOperationException} if no exe for this solver
 	 */
 	public static File[] getExes(SolverDescription sd) throws IOException {
 		SolverExecutable se = sd.getSolverExecutable(); 
 		if (se != null) {
-			SolverExecutable.NameInfo nameInfos[] = se.getNameInfo(); 
+			SolverExecutable.NameInfo[] nameInfos = se.getNameInfo();
 			File files[] = new File[nameInfos.length];
 			for (int i = 0; i < nameInfos.length; ++i) {
 				SolverExecutable.NameInfo ni = nameInfos[i];
@@ -106,7 +106,7 @@ public static File[] getExes(SolverDescription sd) throws IOException {
 	}
 
 	/**
-	 * calls {@link #getExes(SolverConfig)} if solver requires executables,
+	 * calls {@link #getExes(SolverDescription)} if solver requires executables,
 	 * no-op otherwise
 	 */
 	public static void prepareSolverExecutable(SolverDescription solverDescription) throws IOException {
@@ -179,33 +179,29 @@ private static List<SolverDescription> matchByKisaoId(KisaoTerm candidate) {
 	}
 
 	private static SolverDescription attemptLastResortMatch(KisaoTerm last) {
-		switch(last.getId()) {
-		case "KISAO_0000433":
-			return SolverDescription.CVODE;
-		case "KISAO_0000094":
-			return SolverDescription.CVODE;
-		case "KISAO_0000284":
-			return SolverDescription.CVODE;
-		case "KISAO_0000319":
-			return SolverDescription.StochGibson;
-		case "KISAO_0000408":
-			return SolverDescription.IDA;
-		case "KISAO_0000056":
-			return SolverDescription.Smoldyn;
-		case "KISAO_0000352":
-			return SolverDescription.HybridMilstein;
-		case "KISAO_0000398":
-			return SolverDescription.SundialsPDE;
-		case "KISAO_0000369":
-			return SolverDescription.SundialsPDE;
-		case "KISAO_0000281":
-			return SolverDescription.AdamsMoulton;
-		case "KISAO_0000377":
-			return SolverDescription.RungeKuttaFehlberg;
-		default:
-			logger.error("Failed last resort match for descendant " + last.getId());
-			return null;
-		}
+        return switch (last.getId()) {
+            case "KISAO_0000056" -> SolverDescription.Smoldyn; // Livermore Solver
+            case "KISAO_0000094" /* Livermore Solver */, "KISAO_0000284" /* ? missing ? */,
+				 "KISAO_0000433" /* CVODE-like method */, "KISAO_0000694" /* ODE-solver */ ->
+                    SolverDescription.CVODE;
+            case "KISAO_0000281" /*multi-step method*/ ->
+                    SolverDescription.AdamsMoulton;
+            case "KISAO_0000319" /*Monte-carlo*/ ->
+                    SolverDescription.StochGibson;
+            case "KISAO_0000352" /* Hybrid-method */ ->
+                    SolverDescription.HybridMilstein;
+            case "KISAO_0000369" /* partial differential equation discretization method */,
+				 "KISAO_0000398" /* iterative method for solving a system of equations */ ->
+                    SolverDescription.SundialsPDE;
+            case "KISAO_0000377" /* one-step method */ ->
+                    SolverDescription.RungeKuttaFehlberg;
+            case "KISAO_0000408" /* Newton type method */ ->
+                    SolverDescription.IDA;
+            default -> {
+                logger.error("Failed last resort match for descendant {}", last.getId());
+                yield null;
+            }
+        };
 	}
 
 	private static boolean needsExactMatch(boolean cmdRequestedMatch){
diff --git a/vcell-core/src/main/java/org/vcell/sedml/SEDMLImporter.java b/vcell-core/src/main/java/org/vcell/sedml/SEDMLImporter.java
index fae447a090..ad2582cd1d 100644
--- a/vcell-core/src/main/java/org/vcell/sedml/SEDMLImporter.java
+++ b/vcell-core/src/main/java/org/vcell/sedml/SEDMLImporter.java
@@ -180,11 +180,11 @@ public List<BioModel> getBioModels() {
 				// try to find a match in the ontology tree
 				SolverDescription solverDescription = SolverUtilities.matchSolverWithKisaoId(kisaoID, this.exactMatchOnly);
 				if (solverDescription != null) {
-					logger.info("Task (id='"+selectedTask.getId()+"') is compatible, solver match found in ontology: '" + kisaoID + "' matched to " + solverDescription);
+                    logger.info("Task (id='{}') is compatible, solver match found in ontology: '{}' matched to {}", selectedTask.getId(), kisaoID, solverDescription);
 				} else {
 					// give it a try anyway with our deterministic default solver
 					solverDescription = SolverDescription.CombinedSundials;
-					logger.error("Task (id='"+selectedTask.getId()+")' is not compatible, no equivalent solver found in ontology for requested algorithm '"+kisaoID + "'; trying with deterministic default solver "+solverDescription);
+                    logger.error("Task (id='{})' is not compatible, no equivalent solver found in ontology for requested algorithm '{}'; trying with deterministic default solver {}", selectedTask.getId(), kisaoID, solverDescription);
 				}
 				// find out everything else we need about the application we're going to use,
 				// as some more info will be needed when we parse the sbml file
@@ -1010,7 +1010,7 @@ private void translateAlgorithmParams(SolverTaskDescription simTaskDesc, org.jli
 		String kisaoID = algorithm.getKisaoID();
 		ErrorTolerance errorTolerance = new ErrorTolerance();
 		List<AlgorithmParameter> sedmlAlgorithmParameters = algorithm.getListOfAlgorithmParameters();
-		for(AlgorithmParameter sedmlAlgorithmParameter : sedmlAlgorithmParameters) {
+		for (AlgorithmParameter sedmlAlgorithmParameter : sedmlAlgorithmParameters) {
 
 			String apKisaoID = sedmlAlgorithmParameter.getKisaoID();
 			String apValue = sedmlAlgorithmParameter.getValue();
diff --git a/vcell-core/src/main/resources/kisao_algs.obo b/vcell-core/src/main/resources/kisao_algs.obo
index b022707c32..6ac7c17e86 100644
--- a/vcell-core/src/main/resources/kisao_algs.obo
+++ b/vcell-core/src/main/resources/kisao_algs.obo
@@ -1,2847 +1,5320 @@
 format-version: 1.2
+idspace: dc http://purl.org/dc/terms/ 
+idspace: kisao http://www.biomodels.net/kisao/KISAO# 
+idspace: ont http://www.co-ode.org/ontologies/ont.owl# 
+idspace: protege http://protege.stanford.edu/plugins/owl/protege# 
+idspace: skos http://www.w3.org/2004/02/skos/core# 
 remark: This is a core version which contains all but deprecated classes.
 ontology: http://www.biomodels.net/kisao/KISAO#
-property_value: defaultLanguage "en" xsd:string
-property_value: definition "The Kinetic Simulation Algorithm Ontology (KiSAO) classifies algorithms available for the simulation and analysis of models in biology, and their characteristics and the parameters required for their use." xsd:string
-property_value: http://purl.org/dc/terms/rights "Artistic License 2.0" xsd:string
-property_value: owl:versionInfo "2.30" xsd:decimal
+property_value: dc:rights "Artistic License 2.0" xsd:string
+property_value: owl:versionInfo "2.34" xsd:decimal
+property_value: protege:defaultLanguage "en" xsd:string
 property_value: seeAlso "http://co.mbine.org/standards/kisao" xsd:anyURI
 property_value: seeAlso "http://identifiers.org/pubmed/22027554" xsd:anyURI
-owl-axioms: Prefix(owl:=<http://www.w3.org/2002/07/owl#>)\nPrefix(rdf:=<http://www.w3.org/1999/02/22-rdf-syntax-ns#>)\nPrefix(xml:=<http://www.w3.org/XML/1998/namespace>)\nPrefix(xsd:=<http://www.w3.org/2001/XMLSchema#>)\nPrefix(rdfs:=<http://www.w3.org/2000/01/rdf-schema#>)\n\n\nOntology(\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000003>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000015>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000017>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000019>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000020>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000021>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000028>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000029>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000032>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000033>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000038>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000039>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000040>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000045>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000046>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000048>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000051>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000071>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000074>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000075>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000081>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000082>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000084>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000086>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000087>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000088>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000089>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000090>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000091>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000093>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000094>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000095>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000231>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000232>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000233>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000234>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000241>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000261>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000264>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000273>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000274>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000276>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000278>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000279>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000280>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000281>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000282>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000283>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000285>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000286>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000287>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000288>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000289>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000290>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000296>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000297>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000299>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000301>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000302>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KISAO_0000303>))\nDeclaration(Class(<http://www.biomodels.net/kisao/KISAO#KI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<http://www.biomodels.net/kisao/KISAO#KISAO_0000019> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000019>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000019> \"2007-11-30\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000020> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000020>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000020> ObjectUnionOf(ObjectIntersectionOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> <http://www.biomodels.net/kisao/KISAO#KISAO_0000288>) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> <http://www.biomodels.net/kisao/KISAO#KISAO_0000353>)) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> <http://www.biomodels.net/kisao/KISAO#KISAO_0000280>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000021> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000021>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000027> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000027>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000027> \"2007-11-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000028> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000028>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000029> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000029>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000029> \"2007-11-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000032> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000032>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000032> \"2007-11-12\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000032> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000033> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000033>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000033> \"2007-11-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000038> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000038>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000039> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000039>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000039> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000040> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000040>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000045> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000045>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000045> \"2007-10-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000046> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000046>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000046> \"2007-10-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000048> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000048>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000051> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000051>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000056> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000056>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000056> \"2007-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000064> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000064>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000064> \"2007-11-12\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000071> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000071>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000071> \"2007-11-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000074> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000074>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000074> \"2007-10-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000075> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000075>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000081> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000081>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000082> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000082>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000084> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000084>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000086> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000086>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000087> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000087>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000087> \"2007-11-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000088> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000088>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000088> \"2007-11-30\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000089> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000089>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000089> \"2007-10-27\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000090> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000090>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000091> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000091>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000091> \"2007-11-30\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000093> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000093>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000093> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000094>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000095> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000095>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000095> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000231> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000231>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000232> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000232>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000233> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000233>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000234> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000234>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000241> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000241>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000261> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000261>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000261> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000359> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"1\"^^xsd:integer))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000264> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000264>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000264> \"2011-04-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000273>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> \"2011-05-05\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000274> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000274>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000274> \"2011-05-05\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000276> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000276>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000276> \"2011-05-09\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000276> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000278> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000278>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000278> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000279> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000279>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000279> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000280> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000280>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000280> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000281>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000282> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000282>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000282> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000283> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000283>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000283> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000285> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000285>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000285> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000286> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000286>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000286> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000287> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000287>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000287> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000288> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000288>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000288> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000289> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000289>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000289> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000290> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000290>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000290> \"2011-05-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000290> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000296> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000296>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000296> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000297> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000297>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000297> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000299> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000299>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000299> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000301> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000301>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000301> \"2011-05-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000301> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"2\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000302> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000302>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000302> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000303> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000303>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000303> \"2011-05-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000303> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"3\"^^xsd:integer))))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000303> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000304> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000304>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000304> \"2011-05-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000305> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000305>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000305> \"2011-05-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000305> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"5\"^^xsd:integer))))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000305> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"6\"^^xsd:integer))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000306>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> \"2011-05-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000307> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000307>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000307> \"2011-05-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000310> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000310>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000310> \"2011-05-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000314>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> \"2011-05-20\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000317> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000317>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000317> \"2011-05-23\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000318> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000318>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000318> \"2011-05-26\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000319>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> \"2011-05-26\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000320> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000320>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000320> \"2011-05-26\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000321> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000321>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000321> \"2011-05-26\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000323> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000323>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000323> \"2011-06-02\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000324> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000324>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000324> \"2011-06-02\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000329> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000329>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000329> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000330> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000330>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000330> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000331> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000331>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000331> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000333> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000333>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000333> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000335> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000335>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000335> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000336> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000336>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000336> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000337> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000337>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000337> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000338> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000338>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000338> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000339> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000339>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000339> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000341> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000341>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000341> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000342> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000342>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000342> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000343> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000343>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000343> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000345> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000345>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000345> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000348> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000348>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000348> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000349> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000349>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000349> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000350> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000350>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000350> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000351> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000351>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000351> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000353> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000353>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000353> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000355> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000355>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000355> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000356> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000356>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000356> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000357> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000357>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000357> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000358> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000358>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000358> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000363>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> \"2011-06-13\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000364> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000364>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000364> \"2011-06-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000365> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000365>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000365> \"2011-06-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000367> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000367>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000367> \"2011-06-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000369>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> \"2011-06-27\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000377>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> \"2011-06-30\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000378> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000378>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000378> \"2011-06-30\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000378> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"2\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000380> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000380>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000380> \"2011-07-01\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000381> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000381>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000381> \"2011-07-01\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000381> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"2\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000382> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000382>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000382> \"2011-07-01\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000384> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000384>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000384> \"2011-07-01\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000388> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000388>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000388> \"2011-07-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000395> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000395>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000395> \"2011-07-19\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000397>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> \"2011-07-19\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000398>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> \"2011-07-19\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000407>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> \"2012-01-17\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000408>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000409> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000409>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000409> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000410> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000410>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000410> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000411> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000411>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000411> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000412> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000412>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000412> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000413> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000413>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000413> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000416> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000416>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000416> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000417> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000417>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000417> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000418> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000418>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000418> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000419>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000432> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000432>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000432> \"2012-05-24\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000433>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> \"2012-05-24\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000433> ObjectUnionOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> <http://www.biomodels.net/kisao/KISAO#KISAO_0000280>) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> <http://www.biomodels.net/kisao/KISAO#KISAO_0000288>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000434> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000434>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000434> \"2012-09-25\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000435> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000435>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000435> \"2012-09-26\"^^xsd:date)\nEquivalentClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000435> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000302> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"5\"^^xsd:integer)))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000436> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000436>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000436> \"2012-09-26\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000436> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"5\"^^xsd:integer))))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000436> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"8\"^^xsd:integer))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000437> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000437>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000437> \"2012-11-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000447> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000447>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000447> \"2013-01-28\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000447> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000015> <http://www.biomodels.net/kisao/KISAO#KISAO_0000039>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000448> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000448>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000448> \"2013-01-28\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000468> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000468>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000468> \"2014-04-25\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000470> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000470>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000470> \"2015-04-23\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000473> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000473>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000473> \"2015-04-23\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000491> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000491>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000496> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000496>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000497> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000497>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000497> \"2017-01-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000499> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000499>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000499> \"2017-09-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000500> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000500>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000500> \"2017-09-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000501> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000501>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000501> \"2017-09-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000502> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000502>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000502> \"2017-09-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000503> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000503>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000503> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000504> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000504>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000504> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000505> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000505>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000505> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000510> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000510>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000510> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000511> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000511>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000511> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000512> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000512>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000512> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000513> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000513>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000513> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000514> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000514>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000514> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000515> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000515>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000515> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000516> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000516>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000516> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000520> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000520>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000520> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000524> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000524>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000524> \"2020-05-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000526> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000526>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000526> \"2020-08-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000527> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000527>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000527> \"2020-08-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000535> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000535>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000535> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000536> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000536>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000536> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000560> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000560>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000560> \"2020-10-29\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000560> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000088> <http://www.biomodels.net/kisao/KISAO#KISAO_0000089>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000561> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000561>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000561> \"2020-10-29\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000561> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000032>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000562> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000562>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000562> \"2020-10-29\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000562> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000088>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000563> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000563>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000563> \"2020-10-29\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000563> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000086>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000573> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000573>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000573> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000575> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000575>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000575> \"2020-11-06\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000575> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000039> ObjectUnionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> <http://www.biomodels.net/kisao/KISAO#KISAO_0000088> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281>))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000580> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000580>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000580> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000588> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000588>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000588> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000591> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000591>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000591> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000593> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000593>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000593> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000595> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000595>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000595> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000596> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000596>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000596> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000598> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000598>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000598> \"2021-01-13\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000598> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000287>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000599> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000599>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000599> \"2021-01-13\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000599> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000286>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000600> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000600>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000600> \"2021-01-13\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000600> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000287>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000606> 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<http://www.biomodels.net/kisao/KISAO#KISAO_0000397> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> <http://www.biomodels.net/kisao/KISAO#KISAO_0000491>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> <http://www.biomodels.net/kisao/KISAO#KISAO_0000448> <http://www.biomodels.net/kisao/KISAO#KISAO_0000473>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> <http://www.biomodels.net/kisao/KISAO#KISAO_0000448> <http://www.biomodels.net/kisao/KISAO#KISAO_0000473> <http://www.biomodels.net/kisao/KISAO#KISAO_0000491> <http://www.biomodels.net/kisao/KISAO#KISAO_0000497> <http://www.biomodels.net/kisao/KISAO#KISAO_0000499>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> <http://www.biomodels.net/kisao/KISAO#KISAO_0000470> <http://www.biomodels.net/kisao/KISAO#KISAO_0000473> <http://www.biomodels.net/kisao/KISAO#KISAO_0000491> <http://www.biomodels.net/kisao/KISAO#KISAO_0000497>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> <http://www.biomodels.net/kisao/KISAO#KISAO_0000261> <http://www.biomodels.net/kisao/KISAO#KISAO_0000286> <http://www.biomodels.net/kisao/KISAO#KISAO_0000380>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000071> <http://www.biomodels.net/kisao/KISAO#KISAO_0000088> <http://www.biomodels.net/kisao/KISAO#KISAO_0000089> <http://www.biomodels.net/kisao/KISAO#KISAO_0000090> <http://www.biomodels.net/kisao/KISAO#KISAO_0000091> <http://www.biomodels.net/kisao/KISAO#KISAO_0000093> <http://www.biomodels.net/kisao/KISAO#KISAO_0000232> <http://www.biomodels.net/kisao/KISAO#KISAO_0000233> <http://www.biomodels.net/kisao/KISAO#KISAO_0000234> <http://www.biomodels.net/kisao/KISAO#KISAO_0000560>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000086> <http://www.biomodels.net/kisao/KISAO#KISAO_0000087> <http://www.biomodels.net/kisao/KISAO#KISAO_0000321> <http://www.biomodels.net/kisao/KISAO#KISAO_0000434>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000231> <http://www.biomodels.net/kisao/KISAO#KISAO_0000317> 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  Object Properties\n############################\n\n# Object Property: <http://www.biomodels.net/kisao/KISAO#KISAO_0000359> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000359>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000359> \"2011-06-10\"^^xsd:date)\n\n# Object Property: <http://www.biomodels.net/kisao/KISAO#KISAO_0000360> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000360>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000360> \"2011-06-10\"^^xsd:date)\n\n\n############################\n#   Data Properties\n############################\n\n# Data Property: <http://www.biomodels.net/kisao/KISAO#KISAO_0000251> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000251>)\n\nFunctionalDataProperty(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251>)\nDataPropertyDomain(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> <http://www.biomodels.net/kisao/KISAO#KISAO_0000201>)\n\n# Data Property: <http://www.biomodels.net/kisao/KISAO#KISAO_0000275> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000275>)\n\nDataPropertyDomain(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> <http://www.biomodels.net/kisao/KISAO#KISAO_0000064>)\nDataPropertyRange(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> xsd:int)\n\n\n\n############################\n#   Classes\n############################\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000000> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000000>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000000> \"2008-05-26\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000003> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000003>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000003> \"2009-01-24\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000003> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000015> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000015>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000015> \"2007-11-09\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000015> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000017> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000017>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000017> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000019> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000019>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000019> \"2007-11-30\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000020> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000020>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000020> ObjectUnionOf(ObjectIntersectionOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> <http://www.biomodels.net/kisao/KISAO#KISAO_0000288>) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> <http://www.biomodels.net/kisao/KISAO#KISAO_0000353>)) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> <http://www.biomodels.net/kisao/KISAO#KISAO_0000280>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000021> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000021>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000027> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000027>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000027> \"2007-11-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000028> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000028>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000028> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000029> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000029>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000029> \"2007-11-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000029> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000032> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000032>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000032> \"2007-11-12\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000032> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000033> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000033>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000033> \"2007-11-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000038> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000038>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000038> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000039> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000039>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000039> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000040> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000040>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000045> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000045>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000045> \"2007-10-12\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000045> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000046> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000046>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000046> \"2007-10-16\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000046> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000048> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000048>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000048> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000051> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000051>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000051> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000056> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000056>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000056> \"2007-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000064> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000064>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000064> \"2007-11-12\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000071> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000071>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000071> \"2007-11-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000074> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000074>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000074> \"2007-10-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000075> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000075>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000081> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000081>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000082> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000082>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000084> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000084>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000086> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000086>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000087> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000087>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000087> \"2007-11-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000088> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000088>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000088> \"2007-11-30\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000089> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000089>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000089> \"2007-10-27\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000090> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000090>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000091> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000091>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000091> \"2007-11-30\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000093> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000093>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000093> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000094>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> \"2008-07-08\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000094> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000095> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000095>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000095> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000097> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000097>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000098> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000098>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000099> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000099>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000100> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000100>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000102> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000103> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000103>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000103> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000104> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000104>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000104> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000201> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000201>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000203> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000203>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000203> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000204> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000204>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000204> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000205> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000205>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000205> ObjectAllValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000250> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000000> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000322>))))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000205> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000209> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000209>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000209> ObjectAllValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000250> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000237>)))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000209> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000211> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000211>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000211> ObjectAllValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000250> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000237>)))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000211> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000216> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000216>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000216> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:boolean))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000219> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000219>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000219> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000220> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000220>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000220> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000223> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000223>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000223> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000250> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000000> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000375>))))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000223> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000228> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000228>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000228> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000230> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000230>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000230> ObjectAllValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000250> ObjectIntersectionOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> <http://www.biomodels.net/kisao/KISAO#KISAO_0000029>) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> <http://www.biomodels.net/kisao/KISAO#KISAO_0000039>))))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000230> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000231> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000231>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000231> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000374>))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000232> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000232>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000233> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000233>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000234> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000234>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000235> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000235>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000238> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000238>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000241> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000241>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000242> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000242>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000243> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000243>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000243> ObjectAllValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000250> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> <http://www.biomodels.net/kisao/KISAO#KISAO_0000000>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000244> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000244>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000248> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000248>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000248> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000249> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000249>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000249> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000252> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000252>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000253> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000253>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000253> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000254> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000254>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000254> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000255> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000255>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000255> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000256> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000256>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000256> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000257> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000257>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000257> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000258> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000258>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000258> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000260> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000260>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000261> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000261>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000261> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000359> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"1\"^^xsd:integer))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000264> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000264>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000264> \"2011-04-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000273>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> \"2011-05-05\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000274> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000274>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000274> \"2011-05-05\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000276> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000276>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000276> \"2011-05-09\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000276> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000278> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000278>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000278> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000279> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000279>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000279> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000280> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000280>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000280> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000281>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> \"2011-05-09\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000281> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000282> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000282>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000282> \"2011-05-09\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000282> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000376>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000283> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000283>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000283> \"2011-05-09\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000283> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000376>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000285> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000285>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000285> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000286> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000286>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000286> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000287> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000287>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000287> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000288> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000288>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000288> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000289> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000289>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000289> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000290> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000290>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000290> \"2011-05-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000290> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000296> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000296>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000296> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000297> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000297>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000297> \"2011-05-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000297> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000366>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000299> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000299>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000299> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000301> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000301>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000301> \"2011-05-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000301> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"2\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000302> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000302>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000302> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000303> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000303>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000303> \"2011-05-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000303> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"3\"^^xsd:integer))))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000303> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000304> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000304>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000304> \"2011-05-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000305> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000305>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000305> \"2011-05-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000305> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"5\"^^xsd:integer))))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000305> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"6\"^^xsd:integer))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000306>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> \"2011-05-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000307> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000307>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000307> \"2011-05-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000310> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000310>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000310> \"2011-05-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000311> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000311>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000314>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> \"2011-05-20\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000317> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000317>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000317> \"2011-05-23\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000318> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000318>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000318> \"2011-05-26\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000319>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> \"2011-05-26\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000320> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000320>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000320> \"2011-05-26\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000321> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000321>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000321> \"2011-05-26\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000322> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000322>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000322> \"2011-05-27\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000323> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000323>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000323> \"2011-06-02\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000324> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000324>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000324> \"2011-06-02\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000325> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000325>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000325> \"2011-06-02\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000325> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000326> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000326>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000326> \"2011-06-02\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000326> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000327> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000327>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000327> \"2011-06-02\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000327> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000328> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000328>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000328> \"2011-06-02\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000328> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000329> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000329>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000329> \"2011-06-03\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000329> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000330> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000330>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000330> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000331> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000331>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000331> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000332> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000332>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000332> \"2011-06-03\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000332> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000333> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000333>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000333> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000335> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000335>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000335> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000336> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000336>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000336> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000337> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000337>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000337> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000338> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000338>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000338> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000339> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000339>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000339> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000341> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000341>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000341> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000342> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000342>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000342> \"2011-06-07\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000342> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000376>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000343> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000343>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000343> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000345> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000345>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000345> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000348> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000348>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000348> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000349> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000349>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000349> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000350> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000350>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000350> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000351> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000351>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000351> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000353> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000353>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000353> \"2011-06-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000353> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000355> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000355>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000355> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000356> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000356>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000356> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000357> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000357>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000357> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000358> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000358>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000358> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000363>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> \"2011-06-13\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000364> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000364>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000364> \"2011-06-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000365> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000365>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000365> \"2011-06-16\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000365> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000240>))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000366> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000366>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000366> \"2011-06-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000367> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000367>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000367> \"2011-06-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000369>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> \"2011-06-27\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000370> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000370>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000370> \"2011-06-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000371> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000371>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000372> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000372>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000373> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000373>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000376> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000376>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000376> \"2011-07-19\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000377>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> \"2011-06-30\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000377> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000378> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000378>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000378> \"2011-06-30\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000378> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"2\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000380> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000380>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000380> \"2011-07-01\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000381> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000381>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000381> \"2011-07-01\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000381> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"2\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000382> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000382>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000382> \"2011-07-01\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000384> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000384>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000384> \"2011-07-01\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000388> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000388>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000388> \"2011-07-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000395> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000395>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000395> \"2011-07-19\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000397>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> \"2011-07-19\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000398>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> \"2011-07-19\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000404> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000404>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000404> \"2011-07-19\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000405> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000405>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000405> \"2011-07-19\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000407>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> \"2012-01-17\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000408>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000409> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000409>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000409> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000410> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000410>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000410> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000411> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000411>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000411> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000412> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000412>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000412> \"2012-01-18\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000412> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000000> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000237>))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000413> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000413>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000413> \"2012-01-18\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000413> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000000> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000236>))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000415> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000415>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000415> \"2012-01-18\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000415> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000416> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000416>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000416> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000417> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000417>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000417> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000418> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000418>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000418> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000419>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000420> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000420>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000420> \"2012-01-18\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000420> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000421> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000421>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000421> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000422> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000422>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000422> \"2012-01-18\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000422> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000424> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000424>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000424> \"2012-01-18\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000424> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:boolean))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000425> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000425>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000425> \"2012-01-18\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000425> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:boolean))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000427> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000427>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000427> \"2012-01-18\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000427> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000429> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000429>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000430> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000430>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000432> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000432>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000432> \"2012-05-24\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000433>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> \"2012-05-24\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000433> ObjectUnionOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> <http://www.biomodels.net/kisao/KISAO#KISAO_0000280>) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> <http://www.biomodels.net/kisao/KISAO#KISAO_0000288>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000434> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000434>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000434> \"2012-09-25\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000435> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000435>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000435> \"2012-09-26\"^^xsd:date)\nEquivalentClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000435> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000302> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"5\"^^xsd:integer)))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000436> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000436>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000436> \"2012-09-26\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000436> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"5\"^^xsd:integer))))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000436> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"8\"^^xsd:integer))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000437> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000437>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000437> \"2012-11-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000447> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000447>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000447> \"2013-01-28\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000447> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000015> <http://www.biomodels.net/kisao/KISAO#KISAO_0000039>)))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000447> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000000> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000103>))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000448> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000448>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000448> \"2013-01-28\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000450> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000450>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000450> \"2013-01-28\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000451> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000451>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000451> \"2013-01-28\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000452> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000452>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000452> \"2013-01-28\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000452> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000268> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000450> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000104>))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000453> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000453>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000453> \"2013-01-28\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000453> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000268> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000450> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000103>))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000467> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000467>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000467> \"2013-07-05\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000467> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000468> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000468>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000468> \"2014-04-25\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000469> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000469>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000469> \"2014-04-25\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000470> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000470>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000470> \"2015-04-23\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000473> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000473>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000473> \"2015-04-23\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000475> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000475>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000475> \"2015-09-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000476> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000476>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000476> \"2015-09-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000477> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000477>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000477> \"2015-09-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000478> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000478>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000478> \"2015-09-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000479> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000479>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000479> \"2015-09-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000479> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000480> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000480>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000480> \"2015-09-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000480> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000481> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000481>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000481> \"2015-09-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000481> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:boolean))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000482> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000482>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000484> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000484>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000484> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000485> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000485>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000485> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000486> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000486>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000487> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000487>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000487> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000488> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000488>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000488> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000250> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000000> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000104>))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000491> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000491>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000496> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000496>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000497> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000497>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000497> \"2017-01-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000498> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000498>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000498> \"2017-07-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000499> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000499>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000499> \"2017-09-12\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000499> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000374> <http://www.biomodels.net/kisao/KISAO#KISAO_0000623>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000500> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000500>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000500> \"2017-09-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000501> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000501>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000501> \"2017-09-12\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000501> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000376>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000502> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000502>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000502> \"2017-09-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000503> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000503>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000503> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000504> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000504>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000504> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000505> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000505>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000505> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000510> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000510>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000510> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000511> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000511>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000511> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000512> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000512>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000512> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000513> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000513>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000513> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000514> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000514>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000514> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000515> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000515>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000515> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000516> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000516>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000516> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000517> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000517>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000517> \"2019-01-18\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000517> DataExactCardinality(1 <http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000518> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000518>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000518> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000519> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000519>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000519> \"2019-01-18\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000519> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000520> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000520>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000520> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000521> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000521>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000521> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000523> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000523>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000523> \"2019-01-18\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000523> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:double))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000524> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000524>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000524> \"2020-05-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000525> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000525>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000525> \"2020-05-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000526> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000526>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000526> \"2020-08-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000527> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000527>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000527> \"2020-08-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000529> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000529>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000529> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000531> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000531>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000531> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:float))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000532> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000532>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000532> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:boolean))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000533> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000533>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000533> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:float))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000534> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000534>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000535> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000535>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000535> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000536> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000536>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000536> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000560> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000560>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000560> \"2020-10-29\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000560> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000088> <http://www.biomodels.net/kisao/KISAO#KISAO_0000089>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000561> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000561>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000561> \"2020-10-29\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000561> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000032>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000562> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000562>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000562> \"2020-10-29\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000562> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000088>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000563> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000563>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000563> \"2020-10-29\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000563> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000086>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000564> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000564>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000564> \"2020-10-29\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000564> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000573> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000573>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000573> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000575> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000575>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000575> \"2020-11-06\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000575> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000039> ObjectUnionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> <http://www.biomodels.net/kisao/KISAO#KISAO_0000088> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281>))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000580> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000580>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000580> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000588> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000588>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000588> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000591> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000591>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000591> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000593> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000593>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000593> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000595> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000595>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000595> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000596> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000596>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000596> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000598> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000598>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000598> \"2021-01-13\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000598> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000287>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000599> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000599>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000599> \"2021-01-13\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000599> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000286>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000600> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000600>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000600> \"2021-01-13\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000600> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000287>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000606> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000606>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000606> \"2021-01-25\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000606> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000608> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000608>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000608> \"2021-01-25\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000610> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000610>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000610> \"2021-01-25\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000611> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000611>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000613> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000613>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000613> \"2021-01-25\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000617> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000617>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000617> \"2021-01-30\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000618> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000618>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000618> \"2021-01-30\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000619> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000619>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000619> \"2021-01-30\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000620> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000620>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000620> \"2021-04-27\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000621> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000621>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000621> \"2021-04-27\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000623> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000623>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000623> \"2021-04-28\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000695> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000695>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000695> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000251> xsd:string))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000697> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000697>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000697> \"2023-06-06\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000697> ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000800> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000800>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000800> \"2021-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000801> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000801>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000801> \"2021-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000814> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000814>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000814> \"2021-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000815> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000815>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000815> \"2021-06-03\"^^xsd:date)\n\n\nEquivalentClasses(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000322>) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> <http://www.biomodels.net/kisao/KISAO#KISAO_0000000>))\nSubClassOf(ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> ObjectComplementOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000367>) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000239>)) ObjectComplementOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000366>)))\nSubClassOf(ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> ObjectComplementOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000367>) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000366>)) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000245> <http://www.biomodels.net/kisao/KISAO#KISAO_0000240>))\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000000> <http://www.biomodels.net/kisao/KISAO#KISAO_0000097> <http://www.biomodels.net/kisao/KISAO#KISAO_0000201>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000003> <http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000028> <http://www.biomodels.net/kisao/KISAO#KISAO_0000038> <http://www.biomodels.net/kisao/KISAO#KISAO_0000323> <http://www.biomodels.net/kisao/KISAO#KISAO_0000324> <http://www.biomodels.net/kisao/KISAO#KISAO_0000329> <http://www.biomodels.net/kisao/KISAO#KISAO_0000350> <http://www.biomodels.net/kisao/KISAO#KISAO_0000610> <http://www.biomodels.net/kisao/KISAO#KISAO_0000621>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000015> <http://www.biomodels.net/kisao/KISAO#KISAO_0000029> <http://www.biomodels.net/kisao/KISAO#KISAO_0000333> <http://www.biomodels.net/kisao/KISAO#KISAO_0000335> <http://www.biomodels.net/kisao/KISAO#KISAO_0000606>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000017> <http://www.biomodels.net/kisao/KISAO#KISAO_0000021> <http://www.biomodels.net/kisao/KISAO#KISAO_0000264>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000019> <http://www.biomodels.net/kisao/KISAO#KISAO_0000020> <http://www.biomodels.net/kisao/KISAO#KISAO_0000496> <http://www.biomodels.net/kisao/KISAO#KISAO_0000535> <http://www.biomodels.net/kisao/KISAO#KISAO_0000536>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000019> <http://www.biomodels.net/kisao/KISAO#KISAO_0000282> <http://www.biomodels.net/kisao/KISAO#KISAO_0000283>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000019> <http://www.biomodels.net/kisao/KISAO#KISAO_0000282> <http://www.biomodels.net/kisao/KISAO#KISAO_0000356>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000020> <http://www.biomodels.net/kisao/KISAO#KISAO_0000282> <http://www.biomodels.net/kisao/KISAO#KISAO_0000355>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000032> <http://www.biomodels.net/kisao/KISAO#KISAO_0000033> <http://www.biomodels.net/kisao/KISAO#KISAO_0000276> <http://www.biomodels.net/kisao/KISAO#KISAO_0000296> <http://www.biomodels.net/kisao/KISAO#KISAO_0000297> <http://www.biomodels.net/kisao/KISAO#KISAO_0000299> <http://www.biomodels.net/kisao/KISAO#KISAO_0000301> <http://www.biomodels.net/kisao/KISAO#KISAO_0000302> <http://www.biomodels.net/kisao/KISAO#KISAO_0000304> <http://www.biomodels.net/kisao/KISAO#KISAO_0000318> <http://www.biomodels.net/kisao/KISAO#KISAO_0000367> <http://www.biomodels.net/kisao/KISAO#KISAO_0000378> <http://www.biomodels.net/kisao/KISAO#KISAO_0000381> <http://www.biomodels.net/kisao/KISAO#KISAO_0000382> <http://www.biomodels.net/kisao/KISAO#KISAO_0000384>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000039> <http://www.biomodels.net/kisao/KISAO#KISAO_0000082> <http://www.biomodels.net/kisao/KISAO#KISAO_0000330> <http://www.biomodels.net/kisao/KISAO#KISAO_0000331>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000040> <http://www.biomodels.net/kisao/KISAO#KISAO_0000045> <http://www.biomodels.net/kisao/KISAO#KISAO_0000046> <http://www.biomodels.net/kisao/KISAO#KISAO_0000048> <http://www.biomodels.net/kisao/KISAO#KISAO_0000074> <http://www.biomodels.net/kisao/KISAO#KISAO_0000081> <http://www.biomodels.net/kisao/KISAO#KISAO_0000084> <http://www.biomodels.net/kisao/KISAO#KISAO_0000351> <http://www.biomodels.net/kisao/KISAO#KISAO_0000524> <http://www.biomodels.net/kisao/KISAO#KISAO_0000575>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000051> <http://www.biomodels.net/kisao/KISAO#KISAO_0000075> <http://www.biomodels.net/kisao/KISAO#KISAO_0000095> <http://www.biomodels.net/kisao/KISAO#KISAO_0000336> <http://www.biomodels.net/kisao/KISAO#KISAO_0000611> <http://www.biomodels.net/kisao/KISAO#KISAO_0000613> <http://www.biomodels.net/kisao/KISAO#KISAO_0000618> <http://www.biomodels.net/kisao/KISAO#KISAO_0000619>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> <http://www.biomodels.net/kisao/KISAO#KISAO_0000448>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> <http://www.biomodels.net/kisao/KISAO#KISAO_0000491>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> <http://www.biomodels.net/kisao/KISAO#KISAO_0000448> <http://www.biomodels.net/kisao/KISAO#KISAO_0000473>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> <http://www.biomodels.net/kisao/KISAO#KISAO_0000448> <http://www.biomodels.net/kisao/KISAO#KISAO_0000473> <http://www.biomodels.net/kisao/KISAO#KISAO_0000491> <http://www.biomodels.net/kisao/KISAO#KISAO_0000497> <http://www.biomodels.net/kisao/KISAO#KISAO_0000499>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> <http://www.biomodels.net/kisao/KISAO#KISAO_0000470> <http://www.biomodels.net/kisao/KISAO#KISAO_0000473> <http://www.biomodels.net/kisao/KISAO#KISAO_0000491> <http://www.biomodels.net/kisao/KISAO#KISAO_0000497>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> <http://www.biomodels.net/kisao/KISAO#KISAO_0000261> <http://www.biomodels.net/kisao/KISAO#KISAO_0000286> <http://www.biomodels.net/kisao/KISAO#KISAO_0000380>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000071> <http://www.biomodels.net/kisao/KISAO#KISAO_0000088> <http://www.biomodels.net/kisao/KISAO#KISAO_0000089> <http://www.biomodels.net/kisao/KISAO#KISAO_0000090> <http://www.biomodels.net/kisao/KISAO#KISAO_0000091> <http://www.biomodels.net/kisao/KISAO#KISAO_0000093> <http://www.biomodels.net/kisao/KISAO#KISAO_0000232> <http://www.biomodels.net/kisao/KISAO#KISAO_0000233> <http://www.biomodels.net/kisao/KISAO#KISAO_0000234> <http://www.biomodels.net/kisao/KISAO#KISAO_0000560>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000086> <http://www.biomodels.net/kisao/KISAO#KISAO_0000087> <http://www.biomodels.net/kisao/KISAO#KISAO_0000321> <http://www.biomodels.net/kisao/KISAO#KISAO_0000434>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000098> <http://www.biomodels.net/kisao/KISAO#KISAO_0000099> <http://www.biomodels.net/kisao/KISAO#KISAO_0000100> <http://www.biomodels.net/kisao/KISAO#KISAO_0000102> <http://www.biomodels.net/kisao/KISAO#KISAO_0000235> <http://www.biomodels.net/kisao/KISAO#KISAO_0000238> <http://www.biomodels.net/kisao/KISAO#KISAO_0000311> <http://www.biomodels.net/kisao/KISAO#KISAO_0000322> <http://www.biomodels.net/kisao/KISAO#KISAO_0000366> <http://www.biomodels.net/kisao/KISAO#KISAO_0000370> <http://www.biomodels.net/kisao/KISAO#KISAO_0000451>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000203> <http://www.biomodels.net/kisao/KISAO#KISAO_0000204> <http://www.biomodels.net/kisao/KISAO#KISAO_0000205> <http://www.biomodels.net/kisao/KISAO#KISAO_0000248> <http://www.biomodels.net/kisao/KISAO#KISAO_0000249> <http://www.biomodels.net/kisao/KISAO#KISAO_0000257> <http://www.biomodels.net/kisao/KISAO#KISAO_0000258> <http://www.biomodels.net/kisao/KISAO#KISAO_0000260> <http://www.biomodels.net/kisao/KISAO#KISAO_0000327> <http://www.biomodels.net/kisao/KISAO#KISAO_0000328>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000216> <http://www.biomodels.net/kisao/KISAO#KISAO_0000230> <http://www.biomodels.net/kisao/KISAO#KISAO_0000469> <http://www.biomodels.net/kisao/KISAO#KISAO_0000484>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000223> <http://www.biomodels.net/kisao/KISAO#KISAO_0000253> <http://www.biomodels.net/kisao/KISAO#KISAO_0000332> <http://www.biomodels.net/kisao/KISAO#KISAO_0000415>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000223> <http://www.biomodels.net/kisao/KISAO#KISAO_0000253> <http://www.biomodels.net/kisao/KISAO#KISAO_0000332> <http://www.biomodels.net/kisao/KISAO#KISAO_0000486>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000231> <http://www.biomodels.net/kisao/KISAO#KISAO_0000317> <http://www.biomodels.net/kisao/KISAO#KISAO_0000320> <http://www.biomodels.net/kisao/KISAO#KISAO_0000365> <http://www.biomodels.net/kisao/KISAO#KISAO_0000447> <http://www.biomodels.net/kisao/KISAO#KISAO_0000468> <http://www.biomodels.net/kisao/KISAO#KISAO_0000499> <http://www.biomodels.net/kisao/KISAO#KISAO_0000575> <http://www.biomodels.net/kisao/KISAO#KISAO_0000595> <http://www.biomodels.net/kisao/KISAO#KISAO_0000598> <http://www.biomodels.net/kisao/KISAO#KISAO_0000599> <http://www.biomodels.net/kisao/KISAO#KISAO_0000600> <http://www.biomodels.net/kisao/KISAO#KISAO_0000617>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000241> <http://www.biomodels.net/kisao/KISAO#KISAO_0000274> <http://www.biomodels.net/kisao/KISAO#KISAO_0000278> <http://www.biomodels.net/kisao/KISAO#KISAO_0000573>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000242> <http://www.biomodels.net/kisao/KISAO#KISAO_0000243> <http://www.biomodels.net/kisao/KISAO#KISAO_0000244> <http://www.biomodels.net/kisao/KISAO#KISAO_0000252> <http://www.biomodels.net/kisao/KISAO#KISAO_0000420> <http://www.biomodels.net/kisao/KISAO#KISAO_0000421> <http://www.biomodels.net/kisao/KISAO#KISAO_0000422> <http://www.biomodels.net/kisao/KISAO#KISAO_0000429> <http://www.biomodels.net/kisao/KISAO#KISAO_0000430> <http://www.biomodels.net/kisao/KISAO#KISAO_0000475> <http://www.biomodels.net/kisao/KISAO#KISAO_0000476> <http://www.biomodels.net/kisao/KISAO#KISAO_0000477> <http://www.biomodels.net/kisao/KISAO#KISAO_0000478> <http://www.biomodels.net/kisao/KISAO#KISAO_0000481> <http://www.biomodels.net/kisao/KISAO#KISAO_0000482> <http://www.biomodels.net/kisao/KISAO#KISAO_0000487> <http://www.biomodels.net/kisao/KISAO#KISAO_0000488> <http://www.biomodels.net/kisao/KISAO#KISAO_0000498> <http://www.biomodels.net/kisao/KISAO#KISAO_0000518> <http://www.biomodels.net/kisao/KISAO#KISAO_0000521> <http://www.biomodels.net/kisao/KISAO#KISAO_0000525> <http://www.biomodels.net/kisao/KISAO#KISAO_0000529>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000242> <http://www.biomodels.net/kisao/KISAO#KISAO_0000243> <http://www.biomodels.net/kisao/KISAO#KISAO_0000244> <http://www.biomodels.net/kisao/KISAO#KISAO_0000252> <http://www.biomodels.net/kisao/KISAO#KISAO_0000420> <http://www.biomodels.net/kisao/KISAO#KISAO_0000421> <http://www.biomodels.net/kisao/KISAO#KISAO_0000422> <http://www.biomodels.net/kisao/KISAO#KISAO_0000429> <http://www.biomodels.net/kisao/KISAO#KISAO_0000430> <http://www.biomodels.net/kisao/KISAO#KISAO_0000475> <http://www.biomodels.net/kisao/KISAO#KISAO_0000476> <http://www.biomodels.net/kisao/KISAO#KISAO_0000477> <http://www.biomodels.net/kisao/KISAO#KISAO_0000478> <http://www.biomodels.net/kisao/KISAO#KISAO_0000481> <http://www.biomodels.net/kisao/KISAO#KISAO_0000482> <http://www.biomodels.net/kisao/KISAO#KISAO_0000487> <http://www.biomodels.net/kisao/KISAO#KISAO_0000488> <http://www.biomodels.net/kisao/KISAO#KISAO_0000498> <http://www.biomodels.net/kisao/KISAO#KISAO_0000518> <http://www.biomodels.net/kisao/KISAO#KISAO_0000521> <http://www.biomodels.net/kisao/KISAO#KISAO_0000525> <http://www.biomodels.net/kisao/KISAO#KISAO_0000529> <http://www.biomodels.net/kisao/KISAO#KISAO_0000531>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000242> <http://www.biomodels.net/kisao/KISAO#KISAO_0000243> <http://www.biomodels.net/kisao/KISAO#KISAO_0000244> <http://www.biomodels.net/kisao/KISAO#KISAO_0000252> <http://www.biomodels.net/kisao/KISAO#KISAO_0000420> <http://www.biomodels.net/kisao/KISAO#KISAO_0000421> <http://www.biomodels.net/kisao/KISAO#KISAO_0000422> <http://www.biomodels.net/kisao/KISAO#KISAO_0000429> <http://www.biomodels.net/kisao/KISAO#KISAO_0000430> <http://www.biomodels.net/kisao/KISAO#KISAO_0000475> <http://www.biomodels.net/kisao/KISAO#KISAO_0000476> <http://www.biomodels.net/kisao/KISAO#KISAO_0000477> <http://www.biomodels.net/kisao/KISAO#KISAO_0000478> <http://www.biomodels.net/kisao/KISAO#KISAO_0000481> <http://www.biomodels.net/kisao/KISAO#KISAO_0000482> <http://www.biomodels.net/kisao/KISAO#KISAO_0000487> <http://www.biomodels.net/kisao/KISAO#KISAO_0000488> <http://www.biomodels.net/kisao/KISAO#KISAO_0000498> <http://www.biomodels.net/kisao/KISAO#KISAO_0000518> <http://www.biomodels.net/kisao/KISAO#KISAO_0000521> <http://www.biomodels.net/kisao/KISAO#KISAO_0000525> <http://www.biomodels.net/kisao/KISAO#KISAO_0000529> <http://www.biomodels.net/kisao/KISAO#KISAO_0000531> <http://www.biomodels.net/kisao/KISAO#KISAO_0000532> <http://www.biomodels.net/kisao/KISAO#KISAO_0000533> <http://www.biomodels.net/kisao/KISAO#KISAO_0000534>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000242> <http://www.biomodels.net/kisao/KISAO#KISAO_0000243> <http://www.biomodels.net/kisao/KISAO#KISAO_0000244> <http://www.biomodels.net/kisao/KISAO#KISAO_0000252> <http://www.biomodels.net/kisao/KISAO#KISAO_0000420> <http://www.biomodels.net/kisao/KISAO#KISAO_0000421> <http://www.biomodels.net/kisao/KISAO#KISAO_0000422> <http://www.biomodels.net/kisao/KISAO#KISAO_0000429> <http://www.biomodels.net/kisao/KISAO#KISAO_0000430> <http://www.biomodels.net/kisao/KISAO#KISAO_0000475> <http://www.biomodels.net/kisao/KISAO#KISAO_0000476> <http://www.biomodels.net/kisao/KISAO#KISAO_0000477> <http://www.biomodels.net/kisao/KISAO#KISAO_0000478> <http://www.biomodels.net/kisao/KISAO#KISAO_0000481> <http://www.biomodels.net/kisao/KISAO#KISAO_0000482> <http://www.biomodels.net/kisao/KISAO#KISAO_0000487> <http://www.biomodels.net/kisao/KISAO#KISAO_0000488> <http://www.biomodels.net/kisao/KISAO#KISAO_0000498> <http://www.biomodels.net/kisao/KISAO#KISAO_0000525>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000243> <http://www.biomodels.net/kisao/KISAO#KISAO_0000420> <http://www.biomodels.net/kisao/KISAO#KISAO_0000421> <http://www.biomodels.net/kisao/KISAO#KISAO_0000422> <http://www.biomodels.net/kisao/KISAO#KISAO_0000430> <http://www.biomodels.net/kisao/KISAO#KISAO_0000475> <http://www.biomodels.net/kisao/KISAO#KISAO_0000476> <http://www.biomodels.net/kisao/KISAO#KISAO_0000477> <http://www.biomodels.net/kisao/KISAO#KISAO_0000478> <http://www.biomodels.net/kisao/KISAO#KISAO_0000481> <http://www.biomodels.net/kisao/KISAO#KISAO_0000482> <http://www.biomodels.net/kisao/KISAO#KISAO_0000487> <http://www.biomodels.net/kisao/KISAO#KISAO_0000488> <http://www.biomodels.net/kisao/KISAO#KISAO_0000498>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000254> <http://www.biomodels.net/kisao/KISAO#KISAO_0000325> <http://www.biomodels.net/kisao/KISAO#KISAO_0000326> <http://www.biomodels.net/kisao/KISAO#KISAO_0000467>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000279> <http://www.biomodels.net/kisao/KISAO#KISAO_0000280> <http://www.biomodels.net/kisao/KISAO#KISAO_0000364>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000282> <http://www.biomodels.net/kisao/KISAO#KISAO_0000409> <http://www.biomodels.net/kisao/KISAO#KISAO_0000410> <http://www.biomodels.net/kisao/KISAO#KISAO_0000411> 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 name: Kinetic Simulation Algorithm Ontology (KiSAO)
 
 [Term]
-id: KISAO_0000000
+id: kisao:KISAO_0000000
 name: modelling and simulation algorithm
-property_value: altLabel "modeling and simulation algorithm" xsd:string
-property_value: definition "Algorithm used to instantiate a simulation from a mathematical model." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+disjoint_from: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000102 {gci_filler="kisao:KISAO_0000311", gci_relation="kisao:KISAO_0000245"} ! spatial description
+property_value: dc:creator "dk" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:altLabel "modeling and simulation algorithm" xsd:string
+property_value: skos:definition "Algorithm used to instantiate a simulation from a mathematical model." xsd:string
 
 [Term]
-id: KISAO_0000003
+id: kisao:KISAO_0000003
 name: weighted stochastic simulation algorithm
-is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
-disjoint_from: KISAO_0000027 ! Gibson-Bruck next reaction algorithm
-property_value: altLabel "weighted SSA" xsd:string {comment="EXACT"}
-property_value: definition "The weighted stochastic simulation algorithm manipulates the probabilities measure of biochemical systems by sampling, in order to increase the fraction of simulation runs exhibiting rare events." xsd:string
-property_value: http://purl.org/dc/terms/creator "NLN" xsd:string
+is_a: kisao:KISAO_0000333 ! accelerated stochastic simulation algorithm
+disjoint_from: kisao:KISAO_0000027 ! Gibson-Bruck next reaction algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
+property_value: dc:creator "NLN" xsd:string
 property_value: seeAlso "http://identifiers.org/pubmed/19045316" xsd:anyURI {comment="Kuwahara H, Mura I. (2008) An efficient and exact stochastic simulation method to analyse rare events in biochemical systems. J Chem Phys. 129(16):165101."}
+property_value: skos:altLabel "weighted SSA" xsd:string {comment="EXACT"}
+property_value: skos:definition "The weighted stochastic simulation algorithm manipulates the probabilities measure of biochemical systems by sampling, in order to increase the fraction of simulation runs exhibiting rare events." xsd:string
 
 [Term]
-id: KISAO_0000015
+id: kisao:KISAO_0000015
 name: Gillespie first reaction algorithm
-is_a: KISAO_0000241 ! Gillespie-like method
-disjoint_from: KISAO_0000029 ! Gillespie direct algorithm
-property_value: altLabel "Gillespie's first reaction method" xsd:string {comment="EXACT"}
-property_value: definition "Stochastic simulation algorithm using the reaction probability density function (next-reaction density function), giving the probability that the next reaction will happen in a given time interval. To choose the next reaction to fire, the algorithm calculates a tentative reaction time for each reaction and then select the smallest." xsd:string
-property_value: http://purl.org/dc/terms/creator "NLN" xsd:string
-property_value: isImplementedIn "Cain" xsd:string
+is_a: kisao:KISAO_0000241 ! Gillespie-like method
+disjoint_from: kisao:KISAO_0000029 ! Gillespie direct algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
+property_value: dc:creator "NLN" xsd:string
+property_value: kisao:isImplementedIn "Cain" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1016/0021-9991(76)90041-3" xsd:anyURI {comment="Gillespie DT. A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions. Journal of Computational Physics, Volume 2 , pages 403-434 (1976)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1021/j100540a008" xsd:anyURI {comment="Gillespie DT. Exact stochastic simulation of coupled chemical reactions. Journal of Physical Chemistry, Vol. 81, No. 25. (1977), pp. 2340-2361."}
+property_value: skos:altLabel "Gillespie's first reaction method" xsd:string {comment="EXACT"}
+property_value: skos:definition "Stochastic simulation algorithm using the reaction probability density function (next-reaction density function), giving the probability that the next reaction will happen in a given time interval. To choose the next reaction to fire, the algorithm calculates a tentative reaction time for each reaction and then select the smallest." xsd:string
 
 [Term]
-id: KISAO_0000017
+id: kisao:KISAO_0000017
 name: multi-state agent-based simulation method
-is_a: KISAO_0000363 ! rule-based simulation method
-disjoint_from: KISAO_0000021 ! StochSim nearest-neighbour algorithm
-property_value: altLabel "Morton-Firth" xsd:string {comment="EXACT"}
-property_value: definition "The agent-based simulation method instantiates each molecule as an individual software object. The interactions between those objects are determined by interaction probabilities according to experimental data. The probability is depended on the state the molecule is in at that specific time (molecules have multiple-state). Additionally, ''pseudo-molecules'' are introduced to the system in order to simulate unimolecular reactions. For simulation, continuous time is broken down into discrete, independent ''slices''. During each time slice one molecule is selected randomly, a second molecule or pseudo-molecule is selected afterwards (leading to either a unimolecular or a bimolecular reaction). The reaction will only take place if a produced random number exceeds the reaction probability calculated beforehand. In that case, the system is updated after that reaction." xsd:string
-property_value: isImplementedIn "StochSim" xsd:string
+is_a: kisao:KISAO_0000363 ! rule-based simulation method
+disjoint_from: kisao:KISAO_0000021 ! StochSim nearest-neighbour algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000104 ! stochastic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000107 ! progression with adaptive time step
+property_value: kisao:isImplementedIn "StochSim" xsd:string
 property_value: seeAlso "http://identifiers.org/pubmed/9628844" xsd:anyURI {comment="Morton-Firth, C.J, Bray, D. Predicting temporal fluctuations in an intracellular signalling pathway. Journal of Theoretical Biology, volume 192, pages 117-128 (1998)."}
+property_value: skos:altLabel "Morton-Firth" xsd:string {comment="EXACT"}
+property_value: skos:definition "The agent-based simulation method instantiates each molecule as an individual software object. The interactions between those objects are determined by interaction probabilities according to experimental data. The probability is depended on the state the molecule is in at that specific time (molecules have multiple-state). Additionally, ''pseudo-molecules'' are introduced to the system in order to simulate unimolecular reactions. For simulation, continuous time is broken down into discrete, independent ''slices''. During each time slice one molecule is selected randomly, a second molecule or pseudo-molecule is selected afterwards (leading to either a unimolecular or a bimolecular reaction). The reaction will only take place if a produced random number exceeds the reaction probability calculated beforehand. In that case, the system is updated after that reaction." xsd:string
 
 [Term]
-id: KISAO_0000019
+id: kisao:KISAO_0000019
 name: CVODE
-is_a: KISAO_0000433 ! CVODE-like method
-disjoint_from: KISAO_0000020 ! PVODE
-disjoint_from: KISAO_0000282 ! KINSOL
-disjoint_from: KISAO_0000282 ! KINSOL
-disjoint_from: KISAO_0000355 ! DASPK
-relationship: KISAO_0000359 KISAO_0000020 ! PVODE
-property_value: altLabel "code value ordinary differential equation solver" xsd:string {comment="EXACT"}
-property_value: altLabel "VODE" xsd:string {comment="RELATED"}
-property_value: altLabel "VODEPK" xsd:string {comment="RELATED"}
-property_value: definition "The CVODE is a package written in C that solves ODE initial value problems, in real N-space, written as y'=f(t,y),  y(t0)=y0. It is capable for stiff and non-stiff systems and uses two different linear multi-step methods, namely the Adam-Moulton [http://identifiers.org/biomodels.kisao/KISAO_0000280] method and the backward differentiation formula [http://identifiers.org/biomodels.kisao/KISAO_0000288]." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/bionetgen" xsd:anyURI {comment="BioNetGen"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/opencor" xsd:anyURI {comment="OpenCOR"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/pysces" xsd:anyURI {comment="PySCeS"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
-property_value: isImplementedIn "libRoadRunner" xsd:string
-property_value: isImplementedIn "SBML-SAT" xsd:string
-property_value: isImplementedIn "SUNDIALS" xsd:string
+is_a: kisao:KISAO_0000433 ! CVODE-like method
+disjoint_from: kisao:KISAO_0000020 ! PVODE
+disjoint_from: kisao:KISAO_0000282 ! KINSOL
+disjoint_from: kisao:KISAO_0000282 ! KINSOL
+disjoint_from: kisao:KISAO_0000355 ! DASPK
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000209 {maxCardinality="1"} ! relative tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000211 {maxCardinality="1"} ! absolute tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000415 {maxCardinality="1"} ! maximum number of steps
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000475 {maxCardinality="1"} ! integration method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000476 {maxCardinality="1"} ! iteration type
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000477 {maxCardinality="1"} ! linear solver
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000478 {maxCardinality="1"} ! preconditioner
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000479 {maxCardinality="1"} ! upper half-bandwidth
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000480 {maxCardinality="1"} ! lower half-bandwidth
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000481 {maxCardinality="1"} ! interpolate solution
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000543 {maxCardinality="1"} ! stability limit detection flag
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000570 {maxCardinality="1"} ! auto reduce tolerances
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000571 {maxCardinality="1"} ! absolute tolerance adjustment factor
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000020 ! PVODE
+property_value: dc:creator "dk" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/bionetgen" xsd:anyURI {comment="BioNetGen"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/opencor" xsd:anyURI {comment="OpenCOR"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/pysces" xsd:anyURI {comment="PySCeS"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: kisao:isImplementedIn "libRoadRunner" xsd:string
+property_value: kisao:isImplementedIn "SBML-SAT" xsd:string
+property_value: kisao:isImplementedIn "SUNDIALS" xsd:string
 property_value: seeAlso "citeulike:1832863" xsd:anyURI {comment="Cohen S, Hindmarsh C. Cvode, A Stiff/nonstiff Ode Solver In C. Computers in Physics, Vol. 10 (2), pages 138-143 (1996)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1145/1089014.1089020" xsd:anyURI {comment="Hindmarsh, A. C., et al., SUNDIALS: Suite of Nonlinear and Differential/Algebraic Equation Solvers, ACM Trans. Math. Softw., 31:363-396, 2005."}
+property_value: skos:altLabel "code value ordinary differential equation solver" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "VODE" xsd:string {comment="RELATED"}
+property_value: skos:altLabel "VODEPK" xsd:string {comment="RELATED"}
+property_value: skos:definition "The CVODE is a package written in C that solves ODE initial value problems, in real N-space, written as y'=f(t,y),  y(t0)=y0. It is capable for stiff and non-stiff systems and uses two different linear multi-step methods, namely the Adam-Moulton [http://identifiers.org/biomodels.kisao/KISAO_0000280] method and the backward differentiation formula [http://identifiers.org/biomodels.kisao/KISAO_0000288]." xsd:string
 
 [Term]
-id: KISAO_0000020
+id: kisao:KISAO_0000020
 name: PVODE
-is_a: KISAO_0000433 ! CVODE-like method
-disjoint_from: KISAO_0000282 ! KINSOL
-disjoint_from: KISAO_0000283 ! IDA
-disjoint_from: KISAO_0000356 ! DASSL
-relationship: KISAO_0000359 KISAO_0000019 ! CVODE
-property_value: altLabel "parallel code value ordinary differential equation solver" xsd:string {comment="EXACT"}
-property_value: definition "PVODE is a general-purpose solver for ordinary differential equation (ODE) systems that implements methods for both stiff and nonstiff systems. [...] In the stiff case, PVODE uses a backward differentiation formula method [http://identifiers.org/biomodels.kisao/KISAO_0000288] combined with preconditioned GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000253] iteration. Parallelism is achieved by distributing the ODE solution vector into user-specified segments and parallelizing a set of vector kernels accordingly. For PDE-based ODE systems, we provide a module that generates a band block-diagonal preconditioner for use with the GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000253] iteration. PVODE is based on CVODE [http://identifiers.org/biomodels.kisao/KISAO_0000019]." xsd:string
-property_value: isImplementedIn "SUNDIALS" xsd:string
+is_a: kisao:KISAO_0000433 ! CVODE-like method
+disjoint_from: kisao:KISAO_0000282 ! KINSOL
+disjoint_from: kisao:KISAO_0000283 ! IDA
+disjoint_from: kisao:KISAO_0000356 ! DASSL
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000019 ! CVODE
+property_value: kisao:isImplementedIn "SUNDIALS" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1145/1089014.1089020" xsd:anyURI {comment="Hindmarsh, A. C., et al., SUNDIALS: Suite of Nonlinear and Differential/Algebraic Equation Solvers, ACM Trans. Math. Softw., 31:363-396, 2005."}
 property_value: seeAlso "http://identifiers.org/doi/10.1177/109434209901300405" xsd:anyURI {comment="Byrne GD, Hindmarsh AC. PVODE, an ODE Solver for Parallel Computers. International Journal of High Performance Computing Applications, Vol. 13 (4), pages 354-365 (1999)."}
+property_value: skos:altLabel "parallel code value ordinary differential equation solver" xsd:string {comment="EXACT"}
+property_value: skos:definition "PVODE is a general-purpose solver for ordinary differential equation (ODE) systems that implements methods for both stiff and nonstiff systems. [...] In the stiff case, PVODE uses a backward differentiation formula method [http://identifiers.org/biomodels.kisao/KISAO_0000288] combined with preconditioned GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000253] iteration. Parallelism is achieved by distributing the ODE solution vector into user-specified segments and parallelizing a set of vector kernels accordingly. For PDE-based ODE systems, we provide a module that generates a band block-diagonal preconditioner for use with the GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000253] iteration. PVODE is based on CVODE [http://identifiers.org/biomodels.kisao/KISAO_0000019]." xsd:string
 
 [Term]
-id: KISAO_0000021
+id: kisao:KISAO_0000021
 name: StochSim nearest-neighbour algorithm
-is_a: KISAO_0000363 ! rule-based simulation method
-relationship: KISAO_0000359 KISAO_0000264 ! cellular automata update method
-relationship: KISAO_0000360 KISAO_0000017 ! multi-state agent-based simulation method
-property_value: definition "The nearest-neighbour algorithm allows for the representation of spatial information, by adding a two-dimensional lattice in the form of a probabilistic cellular automata. That way, nearest neighbour interactions do additionally influence reactions taking place in the systems. Reactions between entities are calculated using the agent-based simulation algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000017]." xsd:string
-property_value: isImplementedIn "Stochsim 1.2 and more recent versions" xsd:string
+is_a: kisao:KISAO_0000363 ! rule-based simulation method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000102 ! spatial description
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000104 ! stochastic system behaviour
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000264 ! cellular automata update method
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000017 ! multi-state agent-based simulation method
+property_value: kisao:isImplementedIn "Stochsim 1.2 and more recent versions" xsd:string
 property_value: seeAlso "http://identifiers.org/pubmed/11395441" xsd:anyURI {comment="Le Novere N, Shimizu TS. STOCHSIM: modelling of stochastic biomolecular processes. Bioinformatics, volume 17 (6), pages 575-576 (2001)."}
+property_value: skos:definition "The nearest-neighbour algorithm allows for the representation of spatial information, by adding a two-dimensional lattice in the form of a probabilistic cellular automata. That way, nearest neighbour interactions do additionally influence reactions taking place in the systems. Reactions between entities are calculated using the agent-based simulation algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000017]." xsd:string
 
 [Term]
-id: KISAO_0000022
+id: kisao:KISAO_0000022
 name: Elf and Ehrenberg method
-is_a: KISAO_0000095 ! sub-volume stochastic reaction-diffusion algorithm
-disjoint_from: KISAO_0000076 ! Stundzia and Lumsden method
-relationship: KISAO_0000360 KISAO_0000027 ! Gibson-Bruck next reaction algorithm
-relationship: KISAO_0000360 KISAO_0000029 ! Gillespie direct algorithm
-property_value: altLabel "Elf algorithm" xsd:string {comment="EXACT"}
-property_value: altLabel "next-subvolume method" xsd:string {comment="EXACT"}
-property_value: altLabel "NSM" xsd:string {comment="EXACT"}
-property_value: definition "Sub-volume stochastic reaction-diffusion method that is a combination of the Direct Method [http://identifiers.org/biomodels.kisao/KISAO_0000029] for sampling the time for a next reaction or diffusion event in each subvolume, with Gibson and Bruck's Next Reaction Method [http://identifiers.org/biomodels.kisao/KISAO_0000027], which is used to keep track of in which subvolume an event occurs next. The subvolumes are kept sorted in a queue, implemented as a binary tree, according to increasing time of the next event. When an event has occurred in the subvolume at the top of the queue, new event times need to be sampled only for one (the event is a chemical reaction) or two (the event is a diffusion jump) subvolume(s)." xsd:string
-property_value: isImplementedIn "MesoRD" xsd:string
-property_value: isImplementedIn "SmartCell" xsd:string
+is_a: kisao:KISAO_0000095 ! sub-volume stochastic reaction-diffusion algorithm
+disjoint_from: kisao:KISAO_0000076 ! Stundzia and Lumsden method
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000027 ! Gibson-Bruck next reaction algorithm
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000029 ! Gillespie direct algorithm
+property_value: kisao:isImplementedIn "MesoRD" xsd:string
+property_value: kisao:isImplementedIn "SmartCell" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1049/sb:20045021" xsd:anyURI {comment="Elf J, Ehrenberg M. Spontaneous separation of bi-stable biochemical systems into spatial domains of opposite phases. Systems Biology, IEE Proceedings, volume 1 (2), pages 230-236 (2004)."}
+property_value: skos:altLabel "Elf algorithm" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "next-subvolume method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "NSM" xsd:string {comment="EXACT"}
+property_value: skos:definition "Sub-volume stochastic reaction-diffusion method that is a combination of the Direct Method [http://identifiers.org/biomodels.kisao/KISAO_0000029] for sampling the time for a next reaction or diffusion event in each subvolume, with Gibson and Bruck's Next Reaction Method [http://identifiers.org/biomodels.kisao/KISAO_0000027], which is used to keep track of in which subvolume an event occurs next. The subvolumes are kept sorted in a queue, implemented as a binary tree, according to increasing time of the next event. When an event has occurred in the subvolume at the top of the queue, new event times need to be sampled only for one (the event is a chemical reaction) or two (the event is a diffusion jump) subvolume(s)." xsd:string
 
 [Term]
-id: KISAO_0000027
+id: kisao:KISAO_0000027
 name: Gibson-Bruck next reaction algorithm
-is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
-relationship: KISAO_0000359 KISAO_0000015 ! Gillespie first reaction algorithm
-property_value: altLabel "Gibson and Bruck algorithm" xsd:string {comment="EXACT"}
-property_value: altLabel "Gibson-Bruck's next reaction algorithm" xsd:string {comment="EXACT"}
-property_value: altLabel "Gillespie-Gibson stochastic simulation algorithm" xsd:string {comment="EXACT"}
-property_value: altLabel "next reaction method" xsd:string {comment="EXACT"}
-property_value: altLabel "SSA-GB" xsd:string {comment="EXACT"}
-property_value: definition "As with the first reaction method [http://identifiers.org/biomodels.kisao/KISAO_0000015], a putative reaction time is calculated for each reaction, and the reaction with the shortest reaction time will be realized. However, the unused calculated reaction times are not wasted. The set of reactions is organized in a priority queue to allow for the efficient search for the fastest reaction. In addition, by using a so-called dependency graph only those reaction times are recalculated in each step, that are dependent on the reaction, which has been realized." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
-property_value: isImplementedIn "Cain" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
-property_value: isImplementedIn "SmartCell" xsd:string
+is_a: kisao:KISAO_0000333 ! accelerated stochastic simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000015 ! Gillespie first reaction algorithm
+property_value: dc:creator "dk" xsd:string
+property_value: kisao:isImplementedIn "Cain" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: kisao:isImplementedIn "SmartCell" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1021/jp993732q" xsd:anyURI {comment="Gibson MA, Bruck J. Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels. Journal of Physical Chemistry A, Vol. 104, pages 1876-1889 (2000)."}
+property_value: skos:altLabel "Gibson and Bruck algorithm" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Gibson-Bruck's next reaction algorithm" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Gillespie-Gibson stochastic simulation algorithm" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "next reaction method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "SSA-GB" xsd:string {comment="EXACT"}
+property_value: skos:definition "As with the first reaction method [http://identifiers.org/biomodels.kisao/KISAO_0000015], a putative reaction time is calculated for each reaction, and the reaction with the shortest reaction time will be realized. However, the unused calculated reaction times are not wasted. The set of reactions is organized in a priority queue to allow for the efficient search for the fastest reaction. In addition, by using a so-called dependency graph only those reaction times are recalculated in each step, that are dependent on the reaction, which has been realized." xsd:string
 
 [Term]
-id: KISAO_0000028
+id: kisao:KISAO_0000028
 name: slow-scale stochastic simulation algorithm
-is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
-property_value: altLabel "slow-scale stochastic SSA" xsd:string {comment="EXACT"}
-property_value: altLabel "ssSSA" xsd:string {comment="EXACT"}
-property_value: definition "Attempt to overcome the problem of stiff systems by developing an ''approximate theory that allows one to stochastically advance the system in time by simulating the firings of only the slow reaction events''." xsd:string
+is_a: kisao:KISAO_0000333 ! accelerated stochastic simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
 property_value: seeAlso "http://identifiers.org/pubmed/15638651" xsd:anyURI {comment="Cao Y, Gillespie DT, Petzold LR. The slow-scale stochastic simulation algorithm. Journal of Chemical Physics, Vol. 122, No. 1. (1 January 2005)."}
+property_value: skos:altLabel "slow-scale stochastic SSA" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "ssSSA" xsd:string {comment="EXACT"}
+property_value: skos:definition "Attempt to overcome the problem of stiff systems by developing an ''approximate theory that allows one to stochastically advance the system in time by simulating the firings of only the slow reaction events''." xsd:string
 
 [Term]
-id: KISAO_0000029
+id: kisao:KISAO_0000029
 name: Gillespie direct algorithm
-is_a: KISAO_0000241 ! Gillespie-like method
-relationship: KISAO_0000359 KISAO_0000051 ! Bortz-Kalos-Lebowitz algorithm
-property_value: altLabel "DM" xsd:string {comment="EXACT"}
-property_value: altLabel "Doob-Gillespie method" xsd:string {comment="EXACT"}
-property_value: altLabel "Gillespie's algorithm" xsd:string {comment="EXACT"}
-property_value: altLabel "Gillespie's direct method" xsd:string {comment="EXACT"}
-property_value: altLabel "SSA" xsd:string {comment="EXACT"}
-property_value: altLabel "stochastic simulation algorithm" xsd:string {comment="EXACT"}
-property_value: definition "Stochastic simulation algorithm using the reaction probability density function (next-reaction density function), giving the probability that the next reaction will happen in a given time interval. To choose the next reaction to fire, the algorithm directly and separately calculates the identity of the reaction and the time it will fire." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
-property_value: isImplementedIn "BetaWB" xsd:string
-property_value: isImplementedIn "ByoDyn" xsd:string
-property_value: isImplementedIn "Cain" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/bionetgen" xsd:anyURI {comment="BioNetGen"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+is_a: kisao:KISAO_0000241 ! Gillespie-like method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000051 ! Bortz-Kalos-Lebowitz algorithm
+property_value: dc:creator "dk" xsd:string
+property_value: kisao:isImplementedIn "BetaWB" xsd:string
+property_value: kisao:isImplementedIn "ByoDyn" xsd:string
+property_value: kisao:isImplementedIn "Cain" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/bionetgen" xsd:anyURI {comment="BioNetGen"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
 property_value: seeAlso "http://identifiers.org/doi/10.1016/0021-9991(76)90041-3" xsd:anyURI {comment="Gillespie DT. A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions. Journal of Computational Physics, Volume 2 , pages 403-434 (1976)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1021/j100540a008" xsd:anyURI {comment="Gillespie DT. Exact stochastic simulation of coupled chemical reactions. Journal of Physical Chemistry, Vol. 81, No. 25. (1977), pp. 2340-2361."}
+property_value: skos:altLabel "DM" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Doob-Gillespie method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Gillespie's algorithm" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Gillespie's direct method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "SSA" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "stochastic simulation algorithm" xsd:string {comment="EXACT"}
+property_value: skos:definition "Stochastic simulation algorithm using the reaction probability density function (next-reaction density function), giving the probability that the next reaction will happen in a given time interval. To choose the next reaction to fire, the algorithm directly and separately calculates the identity of the reaction and the time it will fire." xsd:string
 
 [Term]
-id: KISAO_0000030
+id: kisao:KISAO_0000030
 name: Euler forward method
-is_a: KISAO_0000261 ! Euler method
-disjoint_from: KISAO_0000031 ! Euler backward method
-property_value: altLabel "explicit Euler method" xsd:string {comment="EXACT"}
-property_value: altLabel "explicit Gaussian first order Runge-Kutta" xsd:string {comment="EXACT"}
-property_value: definition "The Euler method is an explicit one-step method for the numerical integration of ODES with a given initial value. The calculation of the next integration step at time t+1 is based on the state of the system at time point t." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+is_a: kisao:KISAO_0000261 ! Euler method
+disjoint_from: kisao:KISAO_0000031 ! Euler backward method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000239 ! explicit method type
+property_value: dc:creator "dk" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
 property_value: seeAlso "http://identifiers.org/isbn/052143064X" xsd:anyURI {comment="Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical Recipes. Cambridge University Press, New York, 2nd edition (1992)."}
+property_value: skos:altLabel "explicit Euler method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "explicit Gaussian first order Runge-Kutta" xsd:string {comment="EXACT"}
+property_value: skos:definition "The Euler method is an explicit one-step method for the numerical integration of ODES with a given initial value. The calculation of the next integration step at time t+1 is based on the state of the system at time point t." xsd:string
 
 [Term]
-id: KISAO_0000031
+id: kisao:KISAO_0000031
 name: Euler backward method
-is_a: KISAO_0000261 ! Euler method
-property_value: altLabel "implicit Euler method" xsd:string {comment="EXACT"}
-property_value: altLabel "implicit Gaussian first order Runge-Kutta" xsd:string {comment="EXACT"}
-property_value: definition "The Euler backward method is an implicit one-step method for the numerical integration of ODES with a given initial value. The next state of a system is calculated by solving an equation that considers both, the current state of the system and the later one." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
-property_value: isImplementedIn "GSL" xsd:string
+is_a: kisao:KISAO_0000261 ! Euler method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+property_value: dc:creator "dk" xsd:string
+property_value: kisao:isImplementedIn "GSL" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/052143064X" xsd:anyURI {comment="Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical Recipes in Fortran 77. Cambridge University Press (2001)."}
+property_value: skos:altLabel "implicit Euler method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "implicit Gaussian first order Runge-Kutta" xsd:string {comment="EXACT"}
+property_value: skos:definition "The Euler backward method is an implicit one-step method for the numerical integration of ODES with a given initial value. The next state of a system is calculated by solving an equation that considers both, the current state of the system and the later one." xsd:string
 
 [Term]
-id: KISAO_0000032
+id: kisao:KISAO_0000032
 name: explicit fourth-order Runge-Kutta method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-disjoint_from: KISAO_0000033 ! Rosenbrock method
-property_value: altLabel "ERK4" xsd:string {comment="EXACT"}
-property_value: altLabel "RK4" xsd:string {comment="EXACT"}
-property_value: altLabel "Runge-Kutta method" xsd:string {comment="EXACT"}
-property_value: definition "The Runge-Kutta method is a method for the numerical integration of ODES with a given initial value. The calculation of the next integration step at time t+1 is based on the state of the system at time point t, plus the product of the size of the interval and an estimated slope. The slope is a weighted average of 4 single slope points (beginning of interval-midpoint-midpoint-end of interval)." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
-property_value: isImplementedIn "GSL" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+disjoint_from: kisao:KISAO_0000033 ! Rosenbrock method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000239 ! explicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "dk" xsd:string
+property_value: kisao:isImplementedIn "GSL" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
 property_value: seeAlso "http://identifiers.org/isbn/0-471-91046-5 " xsd:anyURI {comment="Butcher JC. The Numerical Analysis of Ordinary Differential Equations: Runge-Kutta and General Linear Methods (1987). "}
+property_value: skos:altLabel "ERK4" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "RK4" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Runge-Kutta method" xsd:string {comment="EXACT"}
+property_value: skos:definition "The Runge-Kutta method is a method for the numerical integration of ODES with a given initial value. The calculation of the next integration step at time t+1 is based on the state of the system at time point t, plus the product of the size of the interval and an estimated slope. The slope is a weighted average of 4 single slope points (beginning of interval-midpoint-midpoint-end of interval)." xsd:string
 
 [Term]
-id: KISAO_0000033
+id: kisao:KISAO_0000033
 name: Rosenbrock method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: altLabel "generalized fourth order Runge-Kutta method" xsd:string {comment="EXACT"}
-property_value: altLabel "Kaps-Rentrop method" xsd:string {comment="EXACT"}
-property_value: definition "Some general implicit processes are given for the solution of simultaneous first-order differential equations. These processes, which use successive substitution, are implicit analogues of the (explicit) Runge-Kutta processes. They require the solution in each time step of one or more set of simultaneous linear equations, usually of a special and simple form. Processes of any required order can be devised, and they can be made to have a wide margin of stability when applied to a linear problem." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "dk" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
 property_value: seeAlso "http://identifiers.org/doi/10.1093/comjnl/5.4.329" xsd:anyURI {comment="Rosenbrock HH. Some general implicit processes for the numerical solution of differential equations. The Computer Journal, pages 329-330 (1963)."}
 property_value: seeAlso "http://identifiers.org/isbn/052143064X" xsd:anyURI {comment="Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical Recipes. Cambridge University Press, New York, 2nd edition, pages 742-746 (1992)."}
+property_value: skos:altLabel "generalized fourth order Runge-Kutta method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Kaps-Rentrop method" xsd:string {comment="EXACT"}
+property_value: skos:definition "Some general implicit processes are given for the solution of simultaneous first-order differential equations. These processes, which use successive substitution, are implicit analogues of the (explicit) Runge-Kutta processes. They require the solution in each time step of one or more set of simultaneous linear equations, usually of a special and simple form. Processes of any required order can be devised, and they can be made to have a wide margin of stability when applied to a linear problem." xsd:string
 
 [Term]
-id: KISAO_0000038
+id: kisao:KISAO_0000038
 name: sorting stochastic simulation algorithm
-is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
-property_value: altLabel "sorting direct method" xsd:string {comment="EXACT"}
-property_value: altLabel "sorting SSA" xsd:string {comment="EXACT"}
-property_value: definition "In order to overcome the problem of high complexity of the stochastic simulation algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000029] when simulating large systems, the sorting direct method maintains a loosely sorted order of the reactions as the simulation executes." xsd:string
+is_a: kisao:KISAO_0000333 ! accelerated stochastic simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
 property_value: seeAlso "http://identifiers.org/doi/10.1016/j.compbiolchem.2005.10.007" xsd:anyURI {comment="McCollum J M, Peterson G D, Cox C D, Simpson M L, Samatova N F. The sorting direct method for stochastic simulation of biochemical systems with varying reaction execution behaviour. Computational Biology and Chemistry, Volume 30 (1), pages 39-49 (2006)."}
+property_value: skos:altLabel "sorting direct method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "sorting SSA" xsd:string {comment="EXACT"}
+property_value: skos:definition "In order to overcome the problem of high complexity of the stochastic simulation algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000029] when simulating large systems, the sorting direct method maintains a loosely sorted order of the reactions as the simulation executes." xsd:string
 
 [Term]
-id: KISAO_0000039
+id: kisao:KISAO_0000039
 name: tau-leaping method
-is_a: KISAO_0000621 ! stochastic simulation leaping method
-disjoint_from: KISAO_0000082 ! k-alpha leaping method
-property_value: altLabel "tauL" xsd:string {comment="EXACT"}
-property_value: definition "Approximate acceleration procedure of the stochastic simulation algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000029] that divides the time into subintervals and ''leaps'' from one to another, firing all the reaction events in each subinterval." xsd:string
-property_value: http://purl.org/dc/terms/creator "NLN" xsd:string
-property_value: isImplementedIn "ByoDyn" xsd:string
-property_value: isImplementedIn "Cain" xsd:string
-property_value: isImplementedIn "SmartCell" xsd:string
+is_a: kisao:KISAO_0000621 ! stochastic simulation leaping method
+disjoint_from: kisao:KISAO_0000082 ! k-alpha leaping method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000228 {cardinality="1"} ! tau-leaping epsilon
+property_value: dc:creator "NLN" xsd:string
+property_value: kisao:isImplementedIn "ByoDyn" xsd:string
+property_value: kisao:isImplementedIn "Cain" xsd:string
+property_value: kisao:isImplementedIn "SmartCell" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1378322" xsd:anyURI {comment="Gillespie DT. Approximate accelerated stochastic simulation of chemically reacting systems. The Journal of Chemical Physics, Vol. 115 (4), pages 1716-1733 (2001). Section V."}
+property_value: skos:altLabel "tauL" xsd:string {comment="EXACT"}
+property_value: skos:definition "Approximate acceleration procedure of the stochastic simulation algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000029] that divides the time into subintervals and ''leaps'' from one to another, firing all the reaction events in each subinterval." xsd:string
 
 [Term]
-id: KISAO_0000040
+id: kisao:KISAO_0000040
 name: Poisson tau-leaping method
-is_a: KISAO_0000039 ! tau-leaping method
-disjoint_from: KISAO_0000045 ! implicit tau-leaping method
-property_value: altLabel "explicit tau-leaping" xsd:string {comment="EXACT"}
-property_value: altLabel "explicit tau-leaping method with basic pre-leap check" xsd:string
-property_value: altLabel "explicit tau-leaping method with basic preleap check" xsd:string {comment="EXACT"}
-property_value: altLabel "poisson tau-leaping" xsd:string {comment="EXACT"}
-property_value: definition "Explicit tau-leaping method with basic pre leap check." xsd:string
-property_value: isImplementedIn "ByoDyn" xsd:string
+is_a: kisao:KISAO_0000039 ! tau-leaping method
+disjoint_from: kisao:KISAO_0000045 ! implicit tau-leaping method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000239 ! explicit method type
+property_value: kisao:isImplementedIn "ByoDyn" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1378322" xsd:anyURI {comment="Gillespie DT. Approximate accelerated stochastic simulation of chemically reacting systems. The Journal of Chemical Physics, Vol. 115 (4), pages 1716-1733 (2001). Section V."}
+property_value: skos:altLabel "explicit tau-leaping" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "explicit tau-leaping method with basic pre-leap check" xsd:string
+property_value: skos:altLabel "explicit tau-leaping method with basic preleap check" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "poisson tau-leaping" xsd:string {comment="EXACT"}
+property_value: skos:definition "Explicit tau-leaping method with basic pre leap check." xsd:string
 
 [Term]
-id: KISAO_0000045
+id: kisao:KISAO_0000045
 name: implicit tau-leaping method
-is_a: KISAO_0000039 ! tau-leaping method
-property_value: definition "Contrary to the explicit tau-leaping [http://identifiers.org/biomodels.kisao/KISAO_0000039 and http://identifiers.org/biomodels.kisao/KISAO_0000245 some http://identifiers.org/biomodels.kisao/KISAO_0000239] , the implicit tau-leaping allows for much larger time-steps when simulating stiff systems." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+is_a: kisao:KISAO_0000039 ! tau-leaping method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000248 {cardinality="1"} ! tau-leaping delta
+property_value: dc:creator "dk" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1627296" xsd:anyURI {comment="Rathinam M, Petzold L R, Cao Y, Gillespie D T. Stiffness in stochastic chemically reacting systems: The implicit tau-leaping method. The Journal of Chemical Physics, Volume 119 (24), pages 12784-12794 (2003)."}
+property_value: skos:definition "Contrary to the explicit tau-leaping [http://identifiers.org/biomodels.kisao/KISAO_0000039 and http://identifiers.org/biomodels.kisao/KISAO_0000245 some http://identifiers.org/biomodels.kisao/KISAO_0000239] , the implicit tau-leaping allows for much larger time-steps when simulating stiff systems." xsd:string
 
 [Term]
-id: KISAO_0000046
+id: kisao:KISAO_0000046
 name: trapezoidal tau-leaping method
-is_a: KISAO_0000039 ! tau-leaping method
-property_value: altLabel "trapezoidal implicit tau-leaping method" xsd:string {comment="EXACT"}
-property_value: definition "Formula for accelerated discrete efficient stochastic simulation of chemically reacting system [which] has better accuracy and stiff stability properties than the explicit and implicit [http://identifiers.org/biomodels.kisao/KISAO_0000045] tau-leaping formulas for discrete stochastic systems, and it limits to the trapezoidal rule in the deterministic regime." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+is_a: kisao:KISAO_0000039 ! tau-leaping method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+property_value: dc:creator "dk" xsd:string
 property_value: seeAlso "citeulike:1755561" xsd:anyURI {comment="Cao Y, Petzold L. Trapezoidal tau-leaping formula for the stochastic simulation of biochemical systems. Foundations of Systems Biology in Engineering (FOSBE), pages 149-152 (2005)."}
+property_value: skos:altLabel "trapezoidal implicit tau-leaping method" xsd:string {comment="EXACT"}
+property_value: skos:definition "Formula for accelerated discrete efficient stochastic simulation of chemically reacting system [which] has better accuracy and stiff stability properties than the explicit and implicit [http://identifiers.org/biomodels.kisao/KISAO_0000045] tau-leaping formulas for discrete stochastic systems, and it limits to the trapezoidal rule in the deterministic regime." xsd:string
 
 [Term]
-id: KISAO_0000048
+id: kisao:KISAO_0000048
 name: adaptive explicit-implicit tau-leaping method
-is_a: KISAO_0000039 ! tau-leaping method
-property_value: definition "Modification of the original tau-selection strategy [http://identifiers.org/biomodels.kisao/KISAO_0000040], designed for explicit tau-leaping, is modified to apply to implicit tau-leaping, allowing for longer steps when the system is stiff. Further, an adaptive strategy is proposed that identifies stiffness and automatically chooses between the explicit and the (new) implicit tau-selection methods to achieve better efficiency." xsd:string
+is_a: kisao:KISAO_0000039 ! tau-leaping method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000239 ! explicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
 property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2745299" xsd:anyURI {comment="Cao Y, Gillespie DT, Petzold LR. Adaptive explicit-implicit tau-leaping method with automatic tau selection. The Journal of Chemical Physics, Vol. 126 (22) (2007)."}
+property_value: skos:definition "Modification of the original tau-selection strategy [http://identifiers.org/biomodels.kisao/KISAO_0000040], designed for explicit tau-leaping, is modified to apply to implicit tau-leaping, allowing for longer steps when the system is stiff. Further, an adaptive strategy is proposed that identifies stiffness and automatically chooses between the explicit and the (new) implicit tau-selection methods to achieve better efficiency." xsd:string
 
 [Term]
-id: KISAO_0000051
+id: kisao:KISAO_0000051
 name: Bortz-Kalos-Lebowitz algorithm
-is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
-disjoint_from: KISAO_0000075 ! Gillespie multi-particle method
-relationship: KISAO_0000359 KISAO_0000029 ! Gillespie direct algorithm
-property_value: altLabel "BKL" xsd:string {comment="EXACT"}
-property_value: altLabel "DMC" xsd:string {comment="EXACT"}
-property_value: altLabel "dynamic Monte Carlo" xsd:string {comment="EXACT"}
-property_value: altLabel "dynamic Monte Carlo method" xsd:string {comment="EXACT"}
-property_value: altLabel "kinetic Monte Carlo" xsd:string {comment="EXACT"}
-property_value: altLabel "kinetic Monte Carlo method" xsd:string {comment="EXACT"}
-property_value: altLabel "KMC" xsd:string {comment="EXACT"}
-property_value: altLabel "n-fold way" xsd:string {comment="EXACT"}
-property_value: definition "The Bortz-Kalos-Lebowitz (or: kinetic Monte-Carlo-) method is a stochastic method for the simulation of time evolution of processes using (pseudo-)random numbers." xsd:string
+is_a: kisao:KISAO_0000335 ! generalized stochastic simulation algorithm
+disjoint_from: kisao:KISAO_0000075 ! Gillespie multi-particle method
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000029 ! Gillespie direct algorithm
 property_value: seeAlso "http://identifiers.org/doi/10.1016/0021-9991(75)90060-1" xsd:anyURI {comment="Bortz AB, Kalos MH, Lebowitz JL. A new algorithm for Monte Carlo simulation of Ising spin systems. Journal of Computational Physics, Vol. 17 (1), pages 10-18 (1975)."}
-
-[Term]
-id: KISAO_0000056
+property_value: skos:altLabel "BKL" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "DMC" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "dynamic Monte Carlo" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "dynamic Monte Carlo method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "kinetic Monte Carlo" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "kinetic Monte Carlo method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "KMC" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "n-fold way" xsd:string {comment="EXACT"}
+property_value: skos:definition "The Bortz-Kalos-Lebowitz (or: kinetic Monte-Carlo-) method is a stochastic method for the simulation of time evolution of processes using (pseudo-)random numbers." xsd:string
+
+[Term]
+id: kisao:KISAO_0000056
 name: Smoluchowski equation based method
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-disjoint_from: KISAO_0000094 ! Livermore solver
-disjoint_from: KISAO_0000094 ! Livermore solver
-disjoint_from: KISAO_0000094 ! Livermore solver
-disjoint_from: KISAO_0000094 ! Livermore solver
-disjoint_from: KISAO_0000094 ! Livermore solver
-disjoint_from: KISAO_0000094 ! Livermore solver
-property_value: definition "Method based on the Smoluchowski equation." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+disjoint_from: kisao:KISAO_0000094 ! Livermore solver
+disjoint_from: kisao:KISAO_0000094 ! Livermore solver
+disjoint_from: kisao:KISAO_0000094 ! Livermore solver
+disjoint_from: kisao:KISAO_0000094 ! Livermore solver
+disjoint_from: kisao:KISAO_0000094 ! Livermore solver
+disjoint_from: kisao:KISAO_0000094 ! Livermore solver
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000104 ! stochastic system behaviour
+property_value: dc:creator "dk" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "urn:issn:0942-9352" xsd:anyURI {comment="Smoluchowski M. Mathematical theory of the kinetics of the coagulation of colloidal solutions. Z. Phys. Chem, Vol. 92, No. 129. (1917)."}
+property_value: skos:definition "Method based on the Smoluchowski equation." xsd:string
 
 [Term]
-id: KISAO_0000057
+id: kisao:KISAO_0000057
 name: Brownian diffusion Smoluchowski method
-is_a: KISAO_0000056 ! Smoluchowski equation based method
-disjoint_from: KISAO_0000058 ! Greens function reaction dynamics
-property_value: definition "In the Brownian diffusion Smoluchowski method, ''each molecule is treated as a point-like particle that diffuses freely in three-dimensional space. When a pair of reactive molecules collide, such as an enzyme and its substrate, a reaction occurs and the simulated reactants are replaced by products. [..] Analytic solutions are presented for some simulation parameters while others are calculated using look-up tables''. Supported chemical processes include molecular diffusion, treatment of surfaces, zeroth-order-, unimolecular-, and bimolecular reactions." xsd:string
-property_value: isImplementedIn "Smoldyn" xsd:string
+is_a: kisao:KISAO_0000056 ! Smoluchowski equation based method
+disjoint_from: kisao:KISAO_0000058 ! Greens function reaction dynamics
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000102 ! spatial description
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000105 ! discrete variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000254 {cardinality="1"} ! Brownian diffusion accuracy
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000257 {cardinality="1"} ! surface-bound epsilon
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000258 {cardinality="1"} ! neighbour distance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000260 {cardinality="1"} ! virtual box size
+property_value: kisao:isImplementedIn "Smoldyn" xsd:string
 property_value: seeAlso "http://identifiers.org/pubmed/16204833" xsd:anyURI {comment="Andrews SS, Bray D. Stochastic simulation of chemical reactions with spatial resolution and single molecule detail. Phys Biol, volume 1 (3-4), pages 137-151 (December 2004)."}
+property_value: skos:definition "In the Brownian diffusion Smoluchowski method, ''each molecule is treated as a point-like particle that diffuses freely in three-dimensional space. When a pair of reactive molecules collide, such as an enzyme and its substrate, a reaction occurs and the simulated reactants are replaced by products. [..] Analytic solutions are presented for some simulation parameters while others are calculated using look-up tables''. Supported chemical processes include molecular diffusion, treatment of surfaces, zeroth-order-, unimolecular-, and bimolecular reactions." xsd:string
 
 [Term]
-id: KISAO_0000058
+id: kisao:KISAO_0000058
 name: Greens function reaction dynamics
-is_a: KISAO_0000056 ! Smoluchowski equation based method
-property_value: altLabel "GFRD" xsd:string {comment="EXACT"}
-property_value: altLabel "Green's function reaction dynamics" xsd:string {comment="EXACT"}
-property_value: definition "Method that simulates biochemical networks on particle level. It considers both changes in time and space by ''exploiting both the exact solution of the Smoluchowski Equation to set up an event-driven algorithm'' which allows for large jumps in time when the considered particles are far away from each other [in space] and thus cannot react. GFRD combines the propagation of particles in space with the reactions taking place between them in one simulation step." xsd:string
+is_a: kisao:KISAO_0000056 ! Smoluchowski equation based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000102 ! spatial description
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000105 ! discrete variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000107 ! progression with adaptive time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
 property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2137716" xsd:anyURI {comment="Van Zon JS, Ten Wolde PR. Green's-function reaction dynamics: A particle-based approach for simulating biochemical networks in time and space. Journal of Chemical Physics, Volume 123 (23) (2005)."}
+property_value: skos:altLabel "GFRD" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Green's function reaction dynamics" xsd:string {comment="EXACT"}
+property_value: skos:definition "Method that simulates biochemical networks on particle level. It considers both changes in time and space by ''exploiting both the exact solution of the Smoluchowski Equation to set up an event-driven algorithm'' which allows for large jumps in time when the considered particles are far away from each other [in space] and thus cannot react. GFRD combines the propagation of particles in space with the reactions taking place between them in one simulation step." xsd:string
 
 [Term]
-id: KISAO_0000064
+id: kisao:KISAO_0000064
 name: Runge-Kutta based method
-is_a: KISAO_0000377 ! one-step method
-disjoint_from: KISAO_0000261 ! Euler method
-relationship: KISAO_0000361 KISAO_0000261 ! Euler method
-property_value: altLabel "modified Euler method" xsd:string {comment="RELATED"}
-property_value: definition "A method of numerically integrating ordinary differential equations, which uses a sampling of slopes through an interval and takes a weighted average to determine the right end point. This averaging gives a very accurate approximation." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
-property_value: isImplementedIn "ByoDyn" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000377 ! one-step method
+disjoint_from: kisao:KISAO_0000261 ! Euler method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000261 ! Euler method
+property_value: dc:creator "dk" xsd:string
+property_value: kisao:isImplementedIn "ByoDyn" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://identifiers.org/isbn/0-471-91046-5" xsd:anyURI {comment="Butcher JC. The Numerical Analysis of Ordinary Differential Equations: Runge-Kutta and General Linear Methods (1987)."}
+property_value: skos:altLabel "modified Euler method" xsd:string {comment="RELATED"}
+property_value: skos:definition "A method of numerically integrating ordinary differential equations, which uses a sampling of slopes through an interval and takes a weighted average to determine the right end point. This averaging gives a very accurate approximation." xsd:string
 
 [Term]
-id: KISAO_0000068
+id: kisao:KISAO_0000068
 name: deterministic cellular automata update algorithm
-is_a: KISAO_0000264 ! cellular automata update method
-property_value: definition "A cellular automaton is a discrete model of a regular grid of cells with a finite number of dimensions. Each cell has a finite number of defined states. The automaton changes its state in a discrete manner, meaning that the state of a cell at time t is determined by a function of the states of its neighbours at time t - 1. These neighbours are a selection of cells relative to the specified cell. Famous examples for deterministic cellular automata are Conway's game of life or Wolfram's elementary cellular automata." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+is_a: kisao:KISAO_0000264 ! cellular automata update method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+property_value: dc:creator "dk" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/978-0252000232" xsd:anyURI {comment="Burks, Arthur W (Editor). Essays on Cellular Automata. University of Illinois Press (1970)."}
+property_value: skos:definition "A cellular automaton is a discrete model of a regular grid of cells with a finite number of dimensions. Each cell has a finite number of defined states. The automaton changes its state in a discrete manner, meaning that the state of a cell at time t is determined by a function of the states of its neighbours at time t - 1. These neighbours are a selection of cells relative to the specified cell. Famous examples for deterministic cellular automata are Conway's game of life or Wolfram's elementary cellular automata." xsd:string
 
 [Term]
-id: KISAO_0000071
+id: kisao:KISAO_0000071
 name: LSODE
-is_a: KISAO_0000094 ! Livermore solver
-disjoint_from: KISAO_0000088 ! LSODA
-relationship: KISAO_0000360 KISAO_0000288 ! backward differentiation formula
-relationship: KISAO_0000360 KISAO_0000364 ! Adams predictor-corrector method
-property_value: altLabel "Livermore solver for ordinary differential equations" xsd:string {comment="EXACT"}
-property_value: definition "LSODE solves stiff and nonstiff systems of the form dy/dt = f. In the stiff case, it treats the Jacobian matrix sf/dy as either a dense (full) or a banded matrix, and as either user-supplied or internally approximated by difference quotients. It uses Adams methods (predictor-corrector) [http://identifiers.org/biomodels.kisao/KISAO_0000364] in the nonstiff case, and Backward Differentiation Formula (BDF) methods (the Gear methods) [http://identifiers.org/biomodels.kisao/KISAO_0000288] in the stiff case." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+is_a: kisao:KISAO_0000094 ! Livermore solver
+disjoint_from: kisao:KISAO_0000088 ! LSODA
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000239 ! explicit method type
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000288 ! backward differentiation formula
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000364 ! Adams predictor-corrector method
+property_value: dc:creator "dk" xsd:string
 property_value: seeAlso "citeulike:1774586" xsd:anyURI {comment="Radhakrishnan K, Hindmarsh AC. Description and Use of LSODE, the Livermore Solver for Ordinary Differential Equations. Lawrence Livermore National Laboratory Report, Vol. UCRL-ID-113855 (1993)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1145/1218052.1218054" xsd:anyURI {comment="Hindmarsh AC. LSODE and LSODI, two new initial value ordinary differential equation solvers. SIGNUM Newsletter, Volume 15 (4), pages 10-11 (1980)."}
+property_value: skos:altLabel "Livermore solver for ordinary differential equations" xsd:string {comment="EXACT"}
+property_value: skos:definition "LSODE solves stiff and nonstiff systems of the form dy/dt = f. In the stiff case, it treats the Jacobian matrix sf/dy as either a dense (full) or a banded matrix, and as either user-supplied or internally approximated by difference quotients. It uses Adams methods (predictor-corrector) [http://identifiers.org/biomodels.kisao/KISAO_0000364] in the nonstiff case, and Backward Differentiation Formula (BDF) methods (the Gear methods) [http://identifiers.org/biomodels.kisao/KISAO_0000288] in the stiff case." xsd:string
 
 [Term]
-id: KISAO_0000074
+id: kisao:KISAO_0000074
 name: binomial tau-leaping method
-is_a: KISAO_0000039 ! tau-leaping method
-relationship: KISAO_0000359 KISAO_0000095 ! sub-volume stochastic reaction-diffusion algorithm
-property_value: altLabel "binomial tau-leap spatial stochastic simulation algorithm" xsd:string {comment="EXACT"}
-property_value: altLabel "BtauL" xsd:string {comment="EXACT"}
-property_value: definition "Coarse grained modified version of the next subvolume method [http://identifiers.org/biomodels.kisao/KISAO_0000022] that allows the user to consider both diffusion and reaction events in relatively long simulation time spans as compared with the original method and other commonly used fully stochastic computational methods." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+is_a: kisao:KISAO_0000039 ! tau-leaping method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000253 {cardinality="1"} ! coarse-graining factor
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000095 ! sub-volume stochastic reaction-diffusion algorithm
+property_value: dc:creator "dk" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2771548" xsd:anyURI {comment="Marquez-Lago T., Burrage K. Binomial tau-leap spatial stochastic simulation algorithm for applications in chemical kinetics. The Journal of Chemical Physics, Vol. 127 (10) (2007)."}
+property_value: skos:altLabel "binomial tau-leap spatial stochastic simulation algorithm" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "BtauL" xsd:string {comment="EXACT"}
+property_value: skos:definition "Coarse grained modified version of the next subvolume method [http://identifiers.org/biomodels.kisao/KISAO_0000022] that allows the user to consider both diffusion and reaction events in relatively long simulation time spans as compared with the original method and other commonly used fully stochastic computational methods." xsd:string
 
 [Term]
-id: KISAO_0000075
+id: kisao:KISAO_0000075
 name: Gillespie multi-particle method
-is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
-relationship: KISAO_0000360 KISAO_0000029 ! Gillespie direct algorithm
-relationship: KISAO_0000360 KISAO_0000334 ! multiparticle lattice gas automata
-property_value: altLabel "Gillespie's multi-particle method" xsd:string {comment="EXACT"}
-property_value: altLabel "GMP" xsd:string {comment="EXACT"}
-property_value: altLabel "particle-based spatial stochastic method" xsd:string {comment="EXACT"}
-property_value: definition "Combination of the multiparticle method for diffusion [http://identifiers.org/biomodels.kisao/KISAO_0000334] and the SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029]." xsd:string
+is_a: kisao:KISAO_0000335 ! generalized stochastic simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000102 ! spatial description
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000029 ! Gillespie direct algorithm
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000334 ! multiparticle lattice gas automata
 property_value: seeAlso "http://identifiers.org/pubmed/16731694" xsd:anyURI {comment="Rodriguez VJ, Kaandorp JA, Dobrzynski M, Blom JG. Spatial stochastic modelling of the phosphoenolpyruvate-dependent phosphotransferase (PTS) pathway in Escherichia coli. Bioinformatics, Vol. 22 (15), pages 1895-1901 (2006)."}
+property_value: skos:altLabel "Gillespie's multi-particle method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "GMP" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "particle-based spatial stochastic method" xsd:string {comment="EXACT"}
+property_value: skos:definition "Combination of the multiparticle method for diffusion [http://identifiers.org/biomodels.kisao/KISAO_0000334] and the SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029]." xsd:string
 
 [Term]
-id: KISAO_0000076
+id: kisao:KISAO_0000076
 name: Stundzia and Lumsden method
-is_a: KISAO_0000095 ! sub-volume stochastic reaction-diffusion algorithm
-property_value: altLabel "RD SSA" xsd:string {comment="EXACT"}
-property_value: altLabel "reaction-diffusion stochastic simulation algorithm" xsd:string {comment="EXACT"}
-property_value: definition "Sub-volume stochastic reaction-diffusion method that using Green's function to link the bulk diffusion coefficient D in Fick's differential law to the corresponding transition rate probability for diffusion of a particle between finite volume elements. This generalized stochastic algorithm enables to numerically calculate the time evolution of a spatially inhomogeneous mixture of reaction-diffusion species in a finite volume. The time step is stochastic and is generated by a probability distribution determined by the intrinsic reaction kinetics and diffusion dynamics." xsd:string
+is_a: kisao:KISAO_0000095 ! sub-volume stochastic reaction-diffusion algorithm
 property_value: seeAlso "http://identifiers.org/doi/10.1006/jcph.1996.0168" xsd:anyURI {comment="Stundzia AB, Lumsden CJ. Stochastic simulation of coupled reaction-diffusion processes. J Comput Phys, Vol. 127 (1), pages 196-207 (1996)."}
+property_value: skos:altLabel "RD SSA" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "reaction-diffusion stochastic simulation algorithm" xsd:string {comment="EXACT"}
+property_value: skos:definition "Sub-volume stochastic reaction-diffusion method that using Green's function to link the bulk diffusion coefficient D in Fick's differential law to the corresponding transition rate probability for diffusion of a particle between finite volume elements. This generalized stochastic algorithm enables to numerically calculate the time evolution of a spatially inhomogeneous mixture of reaction-diffusion species in a finite volume. The time step is stochastic and is generated by a probability distribution determined by the intrinsic reaction kinetics and diffusion dynamics." xsd:string
 
 [Term]
-id: KISAO_0000081
+id: kisao:KISAO_0000081
 name: estimated midpoint tau-leaping method
-is_a: KISAO_0000039 ! tau-leaping method
-property_value: altLabel "explicit tau-leaping method with estimated-mid point technique" xsd:string {comment="EXACT"}
-property_value: definition "Estimated-Midpoint tau-Leap Method: For the selected leaping time tau which satisfies the Leap Condition, compute the expected state change lambda' = tau sumj( aj(x)vj ) during [t, t + tau). Then, with x' =x + [lambda'/2], generate for each j = 1,...,M a sample value kj of the Poisson random variable P(aj(x'), tau). Compute the actual state change, lambda = sumj( kjvj ), and effect the leap by replacing t by t + tau and x by x + lambda." xsd:string
+is_a: kisao:KISAO_0000039 ! tau-leaping method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000239 ! explicit method type
 property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1378322" xsd:anyURI {comment="Gillespie DT. Approximate accelerated stochastic simulation of chemically reacting systems. The Journal of Chemical Physics, Vol. 115 (4), pages 1716-1733 (2001). Section VI."}
+property_value: skos:altLabel "explicit tau-leaping method with estimated-mid point technique" xsd:string {comment="EXACT"}
+property_value: skos:definition "Estimated-Midpoint tau-Leap Method: For the selected leaping time tau which satisfies the Leap Condition, compute the expected state change lambda' = tau sumj( aj(x)vj ) during [t, t + tau). Then, with x' =x + [lambda'/2], generate for each j = 1,...,M a sample value kj of the Poisson random variable P(aj(x'), tau). Compute the actual state change, lambda = sumj( kjvj ), and effect the leap by replacing t by t + tau and x by x + lambda." xsd:string
 
 [Term]
-id: KISAO_0000082
+id: kisao:KISAO_0000082
 name: k-alpha leaping method
-is_a: KISAO_0000621 ! stochastic simulation leaping method
-relationship: KISAO_0000359 KISAO_0000039 ! tau-leaping method
-property_value: definition "Alternative to the tau-leaping [http://identifiers.org/biomodels.kisao/KISAO_0000039], where one leaps a fixed number of reaction-events." xsd:string
+is_a: kisao:KISAO_0000621 ! stochastic simulation leaping method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000039 ! tau-leaping method
 property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1378322" xsd:anyURI {comment="Gillespie DT. Approximate accelerated stochastic simulation of chemically reacting systems. The Journal of Chemical Physics, Vol. 115 (4), pages 1716-1733 (2001). Section VIII."}
+property_value: skos:definition "Alternative to the tau-leaping [http://identifiers.org/biomodels.kisao/KISAO_0000039], where one leaps a fixed number of reaction-events." xsd:string
 
 [Term]
-id: KISAO_0000084
+id: kisao:KISAO_0000084
 name: nonnegative Poisson tau-leaping method
-is_a: KISAO_0000039 ! tau-leaping method
-relationship: KISAO_0000359 KISAO_0000040 ! Poisson tau-leaping method
-property_value: altLabel "modified poisson tau-leaping" xsd:string
-property_value: definition "The explicit tau-leaping procedure attempts to speed up the stochastic simulation of a chemically reacting system by approximating the number of firings of each reaction channel during a chosen time increment Tau as a Poisson random variable. Since the Poisson random variable can have arbitrarily large sample values, there is always the possibility that this procedure will cause one or more reaction channels to fire so many times during Tau that the population of some reactant species will be driven negative. Two recent papers have shown how that unacceptable occurrence can be avoided by replacing the Poisson random variables with binomial random variables, whose values are naturally bounded. This paper describes a modified Poisson tau-leaping procedure that also avoids negative populations, but is easier to implement than the binomial procedure. The new Poisson procedure also introduces a second control parameter, whose value essentially dials the procedure from the original Poisson tau-leaping at one extreme to the exact stochastic simulation algorithm at the other; therefore, the modified Poisson procedure will generally be more accurate than the original Poisson procedure [http://identifiers.org/biomodels.kisao/KISAO_0000040]." xsd:string
+is_a: kisao:KISAO_0000039 ! tau-leaping method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000239 ! explicit method type
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000249 {cardinality="1"} ! critical firing threshold
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000040 ! Poisson tau-leaping method
 property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1992473" xsd:anyURI {comment="Cao Y, Gillespie DT, Petzold LR. Avoiding negative populations in explicit Poisson tau-leaping. Journal of Chemical Physics, Vol. 123, 4104 (2005)."}
+property_value: skos:altLabel "modified poisson tau-leaping" xsd:string
+property_value: skos:definition "The explicit tau-leaping procedure attempts to speed up the stochastic simulation of a chemically reacting system by approximating the number of firings of each reaction channel during a chosen time increment Tau as a Poisson random variable. Since the Poisson random variable can have arbitrarily large sample values, there is always the possibility that this procedure will cause one or more reaction channels to fire so many times during Tau that the population of some reactant species will be driven negative. Two recent papers have shown how that unacceptable occurrence can be avoided by replacing the Poisson random variables with binomial random variables, whose values are naturally bounded. This paper describes a modified Poisson tau-leaping procedure that also avoids negative populations, but is easier to implement than the binomial procedure. The new Poisson procedure also introduces a second control parameter, whose value essentially dials the procedure from the original Poisson tau-leaping at one extreme to the exact stochastic simulation algorithm at the other; therefore, the modified Poisson procedure will generally be more accurate than the original Poisson procedure [http://identifiers.org/biomodels.kisao/KISAO_0000040]." xsd:string
 
 [Term]
-id: KISAO_0000086
+id: kisao:KISAO_0000086
 name: Fehlberg method
-is_a: KISAO_0000435 ! embedded Runge-Kutta 5(4) method
-disjoint_from: KISAO_0000087 ! Dormand-Prince method
-property_value: altLabel "RKF45" xsd:string {comment="EXACT"}
-property_value: altLabel "Runge-Kutta-Fehlberg method" xsd:string {comment="EXACT"}
-property_value: definition "The method was developed by the German mathematician Erwin Fehlberg and is based on the class of Runge-Kutta methods. The Runge-Kutta-Fehlberg method uses an O(h4) method together with an O(h5) method that uses all of the points of the O(h4) method, and hence is often referred to as an RKF45 method. Similar schemes with different orders have since been developed. By performing one extra calculation that would be required for an RK5 method, the error in the solution can be estimated and controlled and an appropriate step size can be determined automatically, making this method efficient for ordinary problems of automated numerical integration of ordinary differential equations." xsd:string
-property_value: isImplementedIn "GSL" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+is_a: kisao:KISAO_0000435 ! embedded Runge-Kutta 5(4) method
+disjoint_from: kisao:KISAO_0000087 ! Dormand-Prince method
+property_value: kisao:isImplementedIn "GSL" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
 property_value: seeAlso "http://identifiers.org/doi/10.1007/BF02241732" xsd:anyURI {comment="Erwin Fehlberg (1970). Klassische Runge-Kutta-Formeln vierter und niedrigerer Ordnung mit Schrittweiten-Kontrolle und ihre Anwendung auf Wärmeleitungsprobleme, Computing (Arch. Elektron. Rechnen), vol. 6, pp. 61-71."}
 property_value: seeAlso "http://identifiers.org/pubmed/14990450" xsd:anyURI {comment="Takahashi K, Kaizu K, Hu B, Tomita M. A multi-algorithm, multi-timescale method for cell simulation. Bioinformatics volume 20(4), pages 538-46 (2004)."}
+property_value: skos:altLabel "RKF45" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Runge-Kutta-Fehlberg method" xsd:string {comment="EXACT"}
+property_value: skos:definition "The method was developed by the German mathematician Erwin Fehlberg and is based on the class of Runge-Kutta methods. The Runge-Kutta-Fehlberg method uses an O(h4) method together with an O(h5) method that uses all of the points of the O(h4) method, and hence is often referred to as an RKF45 method. Similar schemes with different orders have since been developed. By performing one extra calculation that would be required for an RK5 method, the error in the solution can be estimated and controlled and an appropriate step size can be determined automatically, making this method efficient for ordinary problems of automated numerical integration of ordinary differential equations." xsd:string
 
 [Term]
-id: KISAO_0000087
+id: kisao:KISAO_0000087
 name: Dormand-Prince method
-is_a: KISAO_0000435 ! embedded Runge-Kutta 5(4) method
-property_value: altLabel "DOPRI" xsd:string
-property_value: altLabel "Prince-Dormand method" xsd:string {comment="EXACT"}
-property_value: definition "Dormand-Prince is an explicit method for the numerical integration of ODES with a given initial value.\nIt is an 'embedded Runge-Kutta method' [http://identifiers.org/biomodels.kisao/KISAO_0000302] RK5 (4) which (a) has a 'small' principal truncation term in the Fifth order and (b) has an extended region of absolute stability." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
-property_value: isImplementedIn "ECell3" xsd:string
-property_value: isImplementedIn "GSL" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
-property_value: isImplementedIn "Matlab" xsd:string
+is_a: kisao:KISAO_0000435 ! embedded Runge-Kutta 5(4) method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000538 {maxCardinality="1"} ! safety factor on new step selection
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000539 {maxCardinality="1"} ! minimum factor to change step size by
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000540 {maxCardinality="1"} ! maximum factor to change step size by
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000541 {maxCardinality="1"} ! beta parameter for stabilized step size control
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000559 {maxCardinality="1"} ! initial step size
+property_value: dc:creator "dk" xsd:string
+property_value: kisao:isImplementedIn "ECell3" xsd:string
+property_value: kisao:isImplementedIn "GSL" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: kisao:isImplementedIn "Matlab" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1016/0771-050X(80)90013-3" xsd:anyURI {comment="Dormand J, Prince P. A family of embedded Runge-Kutta formulae. Journal of Computational and Applied Mathematics, Volume 6, pages 19-26 (1980)."}
 property_value: seeAlso "http://identifiers.org/pubmed/14990450" xsd:anyURI {comment="Takahashi K, Kaizu K, Hu B, Tomita M. A multi-algorithm, multi-timescale method for cell simulation. Bioinformatics volume 20(4), pages 538-46 (2004)."}
+property_value: skos:altLabel "DOPRI" xsd:string
+property_value: skos:altLabel "Prince-Dormand method" xsd:string {comment="EXACT"}
+property_value: skos:definition "Dormand-Prince is an explicit method for the numerical integration of ODES with a given initial value.\nIt is an 'embedded Runge-Kutta method' [http://identifiers.org/biomodels.kisao/KISAO_0000302] RK5 (4) which (a) has a 'small' principal truncation term in the Fifth order and (b) has an extended region of absolute stability." xsd:string
 
 [Term]
-id: KISAO_0000088
+id: kisao:KISAO_0000088
 name: LSODA
-is_a: KISAO_0000094 ! Livermore solver
-relationship: KISAO_0000359 KISAO_0000071 ! LSODE
-relationship: KISAO_0000360 KISAO_0000288 ! backward differentiation formula
-relationship: KISAO_0000360 KISAO_0000289 ! Adams method
-property_value: altLabel "Livermore solver for ordinary differential equations with automatic method switching" xsd:string {comment="EXACT"}
-property_value: definition "LSODA solves systems dy/dt = f with a dense or banded Jacobian when the problem is stiff, but it automatically selects between non-stiff (Adams [http://identifiers.org/biomodels.kisao/KISAO_0000289]) and stiff (BDF [http://identifiers.org/biomodels.kisao/KISAO_0000288]) methods. It uses the non-stiff method initially, and dynamically monitors data in order to decide which method to use." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+is_a: kisao:KISAO_0000094 ! Livermore solver
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000209 {cardinality="1"} ! relative tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000211 {cardinality="1"} ! absolute tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000219 {cardinality="1"} ! maximum Adams order
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000220 {cardinality="1"} ! maximum BDF order
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000559 {maxCardinality="1"} ! initial step size
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000071 ! LSODE
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000288 ! backward differentiation formula
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000289 ! Adams method
+property_value: dc:creator "dk" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0904010" xsd:anyURI {comment="Petzold LR. Automatic Selection of Methods for Solving Stiff and Nonstiff Systems of Ordinary Differential Equations. SIAM Journal on Scientific and Statistical Computing, Vol. 4 (1), pages 136-148 (1983)."}
 property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
 property_value: seeAlso "http://www.nea.fr/abs/html/uscd1227.html" xsd:anyURI {comment="Petzold LR, Hindmarsh, AC. LSODAR: Livermore solver of ordinary differential equations with automatic method switching and root finding, Computing and Mathematics Research Division, 1-316 Lawerence Livermore National Laboratory (1987)."}
+property_value: skos:altLabel "Livermore solver for ordinary differential equations with automatic method switching" xsd:string {comment="EXACT"}
+property_value: skos:definition "LSODA solves systems dy/dt = f with a dense or banded Jacobian when the problem is stiff, but it automatically selects between non-stiff (Adams [http://identifiers.org/biomodels.kisao/KISAO_0000289]) and stiff (BDF [http://identifiers.org/biomodels.kisao/KISAO_0000288]) methods. It uses the non-stiff method initially, and dynamically monitors data in order to decide which method to use." xsd:string
 
 [Term]
-id: KISAO_0000089
+id: kisao:KISAO_0000089
 name: LSODAR
-is_a: KISAO_0000094 ! Livermore solver
-relationship: KISAO_0000359 KISAO_0000088 ! LSODA
-property_value: altLabel "Livermore solver for ordinary differential equations with automatic method switching and root finding" xsd:string {comment="EXACT"}
-property_value: altLabel "ordinary differential equation solver for stiff or non-stiff systems with root finding" xsd:string {comment="EXACT"}
-property_value: definition "LSODAR is a variant of LSODA [http://identifiers.org/biomodels.kisao/KISAO_0000088] with a root finding capability added. Thus it solves problems dy/dt = f with dense or banded Jacobian and automatic method selection, and at the same time, it finds the roots of any of a set of given functions of the form g(t,y). This is often useful for finding stop conditions, or for finding points at which a switch is to be made in the function f." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+is_a: kisao:KISAO_0000094 ! Livermore solver
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000088 ! LSODA
+property_value: dc:creator "dk" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
 property_value: seeAlso "http://www.nea.fr/abs/html/uscd1228.html" xsd:anyURI {comment="Petzold LR, Hindmarsh, AC. LSODAR: Livermore solver of ordinary differential equations with automatic method switching and root finding, Computing and Mathematics Research Division, 1-316 Lawerence Livermore National Laboratory (1987)."}
+property_value: skos:altLabel "Livermore solver for ordinary differential equations with automatic method switching and root finding" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "ordinary differential equation solver for stiff or non-stiff systems with root finding" xsd:string {comment="EXACT"}
+property_value: skos:definition "LSODAR is a variant of LSODA [http://identifiers.org/biomodels.kisao/KISAO_0000088] with a root finding capability added. Thus it solves problems dy/dt = f with dense or banded Jacobian and automatic method selection, and at the same time, it finds the roots of any of a set of given functions of the form g(t,y). This is often useful for finding stop conditions, or for finding points at which a switch is to be made in the function f." xsd:string
 
 [Term]
-id: KISAO_0000090
+id: kisao:KISAO_0000090
 name: LSODI
-is_a: KISAO_0000094 ! Livermore solver
-relationship: KISAO_0000359 KISAO_0000071 ! LSODE
-property_value: altLabel "Livermore solver for ordinary differential equations, implicit version" xsd:string {comment="EXACT"}
-property_value: definition "LSODI solves systems given in linearly implicit form, including differential-algebraic systems." xsd:string
+is_a: kisao:KISAO_0000094 ! Livermore solver
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000071 ! LSODE
 property_value: seeAlso "http://identifiers.org/doi/10.1145/1218052.1218054" xsd:anyURI {comment="Hindmarsh AC. LSODE and LSODI, two new initial value ordinary differential equation solvers. SIGNUM Newsletter, Volume 15 (4), pages 10-11 (1980)."}
 property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
+property_value: skos:altLabel "Livermore solver for ordinary differential equations, implicit version" xsd:string {comment="EXACT"}
+property_value: skos:definition "LSODI solves systems given in linearly implicit form, including differential-algebraic systems." xsd:string
 
 [Term]
-id: KISAO_0000091
+id: kisao:KISAO_0000091
 name: LSODIS
-is_a: KISAO_0000094 ! Livermore solver
-relationship: KISAO_0000359 KISAO_0000071 ! LSODE
-property_value: altLabel "Livermore solver for ordinary differential equations, implicit sparse version" xsd:string {comment="EXACT"}
-property_value: definition "LSODIS is a set of general-purpose FORTRAN routines solver for the initial value problem for ordinary differential equation systems. It is suitable for both stiff and nonstiff systems. LSODIS treat systems in the linearly implicit form A(t,y) dy/dt = g(t,y), A = a square matrix, i.e. with the derivative dy/dt implicit, but linearly so." xsd:string
-property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+is_a: kisao:KISAO_0000094 ! Livermore solver
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000071 ! LSODE
+property_value: dc:creator "dk" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
 property_value: seeAlso "http://www.nea.fr/abs/html/uscd1225.html" xsd:anyURI {comment="Seager M, Balsdon S. LSODIS - A sparse implicit ODE solver. 10th World Congress on System Simulation and Scientific Computation, pages 437-439 (1983)."}
+property_value: skos:altLabel "Livermore solver for ordinary differential equations, implicit sparse version" xsd:string {comment="EXACT"}
+property_value: skos:definition "LSODIS is a set of general-purpose FORTRAN routines solver for the initial value problem for ordinary differential equation systems. It is suitable for both stiff and nonstiff systems. LSODIS treat systems in the linearly implicit form A(t,y) dy/dt = g(t,y), A = a square matrix, i.e. with the derivative dy/dt implicit, but linearly so." xsd:string
 
 [Term]
-id: KISAO_0000093
+id: kisao:KISAO_0000093
 name: LSODPK
-is_a: KISAO_0000094 ! Livermore solver
-relationship: KISAO_0000359 KISAO_0000071 ! LSODE
-relationship: KISAO_0000360 KISAO_0000354 ! Krylov subspace projection method
-property_value: altLabel "Livermore solver for ordinary differential equations for stiff and nonstiff systems with krylov corrector iteration" xsd:string {comment="EXACT"}
-property_value: definition "LSODPK is a set of FORTRAN subroutines for solving the initial value problem for stiff and nonstiff systems of ordinary differential equations. In solving stiff systems, LSODPK uses a corrector iteration composed of Newton iteration and one of four preconditioned Krylov subspace iteration methods [http://identifiers.org/biomodels.kisao/KISAO_0000354]. The user must select the desired Krylov method and supply a pair of routine to evaluate, preprocess, and solve the (left and/or right) preconditioner matrices. Aside from preconditioning, the implementation is matrix-free, meaning that explicit storage of the Jacobian (or related) matrix is not required. The method is experimental because the scope of problems for which it is effective is not well-known, and users are forewarned that LSODPK may or may not be competitive with traditional methods on a given problem. LSODPK also includes an option for a user-supplied linear system solver to be used without Krylov iteration." xsd:string
-property_value: http://purl.org/dc/terms/creator "NLN" xsd:string
+is_a: kisao:KISAO_0000094 ! Livermore solver
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000071 ! LSODE
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000354 ! Krylov subspace projection method
+property_value: dc:creator "NLN" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
+property_value: skos:altLabel "Livermore solver for ordinary differential equations for stiff and nonstiff systems with krylov corrector iteration" xsd:string {comment="EXACT"}
+property_value: skos:definition "LSODPK is a set of FORTRAN subroutines for solving the initial value problem for stiff and nonstiff systems of ordinary differential equations. In solving stiff systems, LSODPK uses a corrector iteration composed of Newton iteration and one of four preconditioned Krylov subspace iteration methods [http://identifiers.org/biomodels.kisao/KISAO_0000354]. The user must select the desired Krylov method and supply a pair of routine to evaluate, preprocess, and solve the (left and/or right) preconditioner matrices. Aside from preconditioning, the implementation is matrix-free, meaning that explicit storage of the Jacobian (or related) matrix is not required. The method is experimental because the scope of problems for which it is effective is not well-known, and users are forewarned that LSODPK may or may not be competitive with traditional methods on a given problem. LSODPK also includes an option for a user-supplied linear system solver to be used without Krylov iteration." xsd:string
 
 [Term]
-id: KISAO_0000094
+id: kisao:KISAO_0000094
 name: Livermore solver
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: definition "Method to solve ordinary differential equations developed at the Lawrence Livermore National Laboratory." xsd:string
-property_value: http://purl.org/dc/terms/creator "NLN" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000694 ! ODE solver
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000107 ! progression with adaptive time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "NLN" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Method to solve ordinary differential equations developed at the Lawrence Livermore National Laboratory." xsd:string
 
 [Term]
-id: KISAO_0000095
+id: kisao:KISAO_0000095
 name: sub-volume stochastic reaction-diffusion algorithm
-is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
-disjoint_from: KISAO_0000336 ! D-leaping method
-property_value: definition "Stochastic method using a combination of discretisation of compartment volumes into voxels and Gillespie-like algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000241] to simulate the evolution of the system." xsd:string
-property_value: http://purl.org/dc/terms/creator "NLN" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000335 ! generalized stochastic simulation algorithm
+disjoint_from: kisao:KISAO_0000336 ! D-leaping method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000102 ! spatial description
+property_value: dc:creator "NLN" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Stochastic method using a combination of discretisation of compartment volumes into voxels and Gillespie-like algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000241] to simulate the evolution of the system." xsd:string
+
+[Term]
+id: kisao:KISAO_0000097
+name: modelling and simulation algorithm characteristic
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:altLabel "modeling and simulation algorithm characteristic" xsd:string
+property_value: skos:definition "Simulation algorithm property, which can, for example, describe the model, such as the type of variables (discrete or continuous), and information on the treatment of spatial descriptions, or can be a numerical characteristic, such as the system's behaviour (deterministic or stochastic) as well as the progression mechanism (fixed or adaptive time steps)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000098
+name: type of variable
+is_a: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+disjoint_from: kisao:KISAO_0000099 ! type of system behaviour
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Type of variables used for the simulation." xsd:string
+
+[Term]
+id: kisao:KISAO_0000099
+name: type of system behaviour
+is_a: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A characteristic describing the rules the algorithm uses to simulate the temporal evolution of a system, specifically whether or not the final state is uniquely determined from a precise initial state." xsd:string
+
+[Term]
+id: kisao:KISAO_0000100
+name: type of progression time step
+is_a: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Type of time steps used by the algorithm." xsd:string
+
+[Term]
+id: kisao:KISAO_0000102
+name: spatial description
+is_a: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+property_value: dc:creator "NLN" xsd:string
+property_value: skos:definition "Algorithm, possessing this characteristic, takes into account the location of the reacting components." xsd:string
+
+[Term]
+id: kisao:KISAO_0000103
+name: deterministic system behaviour
+is_a: kisao:KISAO_0000099 ! type of system behaviour
+disjoint_from: kisao:KISAO_0000104 ! stochastic system behaviour
+property_value: dc:creator "NLN" xsd:string
+property_value: skos:definition "Algorithm, possessing this characteristic, simulates the temporal evolution of a system deterministically, so that from a precise initial state the algorithm will always end up in the same final state." xsd:string
+
+[Term]
+id: kisao:KISAO_0000104
+name: stochastic system behaviour
+is_a: kisao:KISAO_0000099 ! type of system behaviour
+property_value: dc:creator "NLN" xsd:string
+property_value: skos:definition "Algorithm, possessing this characteristic, simulates the temporal evolution of a system using probabilistic rules, so that between two simulations, the same precise initial state may result in a different final state." xsd:string
+
+[Term]
+id: kisao:KISAO_0000105
+name: discrete variable
+is_a: kisao:KISAO_0000098 ! type of variable
+disjoint_from: kisao:KISAO_0000106 ! continuous variable
+property_value: dc:creator "NLN" xsd:string
+property_value: skos:definition "Algorithm, possessing this characteristic, allows values of system's variables to change by discrete (integral) amounts." xsd:string
+
+[Term]
+id: kisao:KISAO_0000106
+name: continuous variable
+is_a: kisao:KISAO_0000098 ! type of variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000104 ! stochastic system behaviour
+property_value: dc:creator "NLN" xsd:string
+property_value: skos:definition "Algorithm, possessing this characteristic, allows the values of a system's variables to change by continuous (non-integral) amounts." xsd:string
+
+[Term]
+id: kisao:KISAO_0000107
+name: progression with adaptive time step
+is_a: kisao:KISAO_0000100 ! type of progression time step
+disjoint_from: kisao:KISAO_0000108 ! progression with fixed time step
+property_value: dc:creator "NLN" xsd:string
+property_value: skos:definition "Algorithm, possessing this characteristic, does not use fixed time steps to update the state of a system during the whole simulation, but on the contrary adapts the length of the time steps to the local situation." xsd:string
+
+[Term]
+id: kisao:KISAO_0000108
+name: progression with fixed time step
+is_a: kisao:KISAO_0000100 ! type of progression time step
+property_value: dc:creator "NLN" xsd:string
+property_value: skos:definition "Algorithm, possessing this characteristic, uses time steps of constant length to update the state of a system during the whole simulation." xsd:string
+
+[Term]
+id: kisao:KISAO_0000201
+name: modelling and simulation algorithm parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000000 ! modelling and simulation algorithm
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:altLabel "modeling and simulation algorithm parameter" xsd:string
+property_value: skos:definition "Parameter that can be used in the simulation experiment settings." xsd:string
+
+[Term]
+id: kisao:KISAO_0000203
+name: particle number lower limit
+is_a: kisao:KISAO_0000252 ! partitioning control parameter
+disjoint_from: kisao:KISAO_0000204 ! particle number upper limit
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000231 {all_only="true"} ! Pahle hybrid method
+property_value: skos:definition "This parameter of 'Pahle hybrid method' [http://identifiers.org/biomodels.kisao/KISAO_0000231] is a double value specifying the lower limit for particle numbers. Species with a particle number below this value are considered as having a low particle number. The 'particle number lower limit' cannot be higher than the 'particle number upper limit' [http://identifiers.org/biomodels.kisao/KISAO_0000204]." xsd:string
 
 [Term]
-id: KISAO_0000231
+id: kisao:KISAO_0000204
+name: particle number upper limit
+is_a: kisao:KISAO_0000252 ! partitioning control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000231 {all_only="true"} ! Pahle hybrid method
+property_value: skos:definition "This parameter of 'Pahle hybrid method' [http://identifiers.org/biomodels.kisao/KISAO_0000231] is a double value specifying the upper limit for particle numbers. Species with a particle number above this value are considered as having a high particle number. The 'particle number upper limit' cannot be lower than the 'particle number lower limit' [http://identifiers.org/biomodels.kisao/KISAO_0000203]." xsd:string
+
+[Term]
+id: kisao:KISAO_0000205
+name: partitioning interval
+is_a: kisao:KISAO_0000252 ! partitioning control parameter
+property_value: skos:definition "This positive integer value specifies after how many steps the internal partitioning of the system should be recalculated." xsd:string
+
+[Term]
+id: kisao:KISAO_0000209
+name: relative tolerance
+is_a: kisao:KISAO_0000597 ! tolerance
+property_value: skos:altLabel "RTOL" xsd:string {comment="EXACT"}
+property_value: skos:definition "This parameter is a numeric value specifying the desired relative tolerance the user wants to achieve. A smaller value means that the trajectory is calculated more accurately." xsd:string
+
+[Term]
+id: kisao:KISAO_0000211
+name: absolute tolerance
+is_a: kisao:KISAO_0000597 ! tolerance
+property_value: skos:altLabel "ATOL" xsd:string {comment="EXACT"}
+property_value: skos:definition "This parameter is a positive numeric value specifying the desired absolute tolerance the user wants to achieve." xsd:string
+
+[Term]
+id: kisao:KISAO_0000216
+name: use reduced model
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+disjoint_from: kisao:KISAO_0000230 ! minimum reactions per leap
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000088 ! LSODA
+property_value: seeAlso "http://identifiers.org/pubmed/14990466" xsd:anyURI {comment="Jacek Puchałka, Andrzej M Kierzek. Bridging the gap between stochastic and deterministic regimes in the kinetic simulations of the biochemical reaction networks. Biophys J. 2004, 86(3):1357-1372."}
+property_value: skos:altLabel "integrate reduced model" xsd:string
+property_value: skos:definition "Boolean value which indicates whether the simulation/analysis should be performed using the complete model or an equivalent reduced model.\n\nReduced models can be determined in many ways such as using mass conservation laws." xsd:string
+
+[Term]
+id: kisao:KISAO_0000219
+name: maximum Adams order
+is_a: kisao:KISAO_0000484 ! maximum order
+disjoint_from: kisao:KISAO_0000220 ! maximum BDF order
+property_value: skos:altLabel "Adams max order" xsd:string
+property_value: skos:altLabel "maximum non-stiff order" xsd:string
+property_value: skos:definition "This parameter is a positive integer value specifying the maximal order the non-stiff Adams integration method [http://identifiers.org/biomodels.kisao/KISAO_0000289] shall attempt before switching to the stiff BDF method [http://identifiers.org/biomodels.kisao/KISAO_0000288]." xsd:string
+
+[Term]
+id: kisao:KISAO_0000220
+name: maximum BDF order
+is_a: kisao:KISAO_0000484 ! maximum order
+property_value: skos:altLabel "BDF max order" xsd:string
+property_value: skos:altLabel "maximum stiff order" xsd:string
+property_value: skos:definition "This parameter is a positive integer value specifying the maximal order the stiff BDF integration method [http://identifiers.org/biomodels.kisao/KISAO_0000288] shall attempt before switching to smaller internal step sizes." xsd:string
+
+[Term]
+id: kisao:KISAO_0000223
+name: number of history bins
+is_a: kisao:KISAO_0000244 ! granularity control parameter
+disjoint_from: kisao:KISAO_0000253 ! coarse-graining factor
+disjoint_from: kisao:KISAO_0000253 ! coarse-graining factor
+property_value: skos:definition "The 'number of history bins' is only enabled for models that contain delayed or multistep reactions for specifying the granularity with which the delayed reaction solver should retain the history of species values, for species that participate in delayed reactions." xsd:string
+
+[Term]
+id: kisao:KISAO_0000228
+name: tau-leaping epsilon
+is_a: kisao:KISAO_0000242 ! error control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000039 {all_only="true"} ! tau-leaping method
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1378322" xsd:anyURI {comment="Gillespie DT. Approximate accelerated stochastic simulation of chemically reacting systems. The Journal of Chemical Physics, Vol. 115 (4), pages 1716-1733 (2001). Section V."}
+property_value: skos:altLabel "epsilon" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "tolerance" xsd:string
+property_value: skos:definition "The leap condition is chosen such that the expected change in the propensity function aj(x) is bounded by Epsilon * a0 where Epsilon is an error control parameter between 0 and 1. This parameter is the basic error control mechanism for the Tau-Leaping algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000039]. As Epsilon decreases the leaps become shorter and the simulation is more accurate." xsd:string
+
+[Term]
+id: kisao:KISAO_0000230
+name: minimum reactions per leap
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: skos:altLabel "threshold" xsd:string
+property_value: skos:definition "'minimum reactions per leap' parameter is used in hybrid methods, which adaptively switch between the tau-leaping algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000039] to the SSA Direct Method [http://identifiers.org/biomodels.kisao/KISAO_0000029] when the number of reactions in a single tau-leaping leap step is less than the threshold." xsd:string
+
+[Term]
+id: kisao:KISAO_0000231
 name: Pahle hybrid method
-is_a: KISAO_0000352 ! hybrid method
-disjoint_from: KISAO_0000317 ! E-Cell multi-algorithm simulation method
-relationship: KISAO_0000246 KISAO_0000027 ! Gibson-Bruck next reaction algorithm
-property_value: definition "The hybrid method combines the stochastic 'Gibson-Bruck's next reaction method' [http://identifiers.org/biomodels.kisao/KISAO_0000027] with different algorithms for the numerical integration of ODEs [http://identifiers.org/biomodels.kisao/KISAO_0000245 some http://identifiers.org/biomodels.kisao/KISAO_0000374]. The biochemical network is dynamically partitioned into a deterministic and a stochastic subnet depending on the current particle numbers in the system. The user can define limits for when a particle number should be considered low or high. The stochastic subnet contains reactions involving low numbered species as substrate or product. All the other reactions form the deterministic subnet. The two subnets are then simulated in parallel using the stochastic and deterministic solver, respectively. The reaction probabilities in the stochastic subnet are approximated as constant between two stochastic reaction events." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000352 ! hybrid method
+disjoint_from: kisao:KISAO_0000317 ! E-Cell multi-algorithm simulation method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000104 ! stochastic system behaviour
+relationship: kisao:KISAO_0000246 kisao:KISAO_0000027 ! Gibson-Bruck next reaction algorithm
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000203 {cardinality="1"} ! particle number lower limit
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000204 {cardinality="1"} ! particle number upper limit
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://identifiers.org/doi/10.1093/bioinformatics/btl485" xsd:anyURI {comment="COPASI--a COmplex PAthway SImulator. Hoops S, Sahle S, Gauges R, Lee C, Pahle J, Simus N, Singhal M, Xu L, Mendes P, Kummer U. Bioinformatics. 2006 Dec 15;22(24):3067-74. Epub 2006 Oct 10."}
+property_value: skos:definition "The hybrid method combines the stochastic 'Gibson-Bruck's next reaction method' [http://identifiers.org/biomodels.kisao/KISAO_0000027] with different algorithms for the numerical integration of ODEs [http://identifiers.org/biomodels.kisao/KISAO_0000245 some http://identifiers.org/biomodels.kisao/KISAO_0000374]. The biochemical network is dynamically partitioned into a deterministic and a stochastic subnet depending on the current particle numbers in the system. The user can define limits for when a particle number should be considered low or high. The stochastic subnet contains reactions involving low numbered species as substrate or product. All the other reactions form the deterministic subnet. The two subnets are then simulated in parallel using the stochastic and deterministic solver, respectively. The reaction probabilities in the stochastic subnet are approximated as constant between two stochastic reaction events." xsd:string
 
 [Term]
-id: KISAO_0000232
+id: kisao:KISAO_0000232
 name: LSOIBT
-is_a: KISAO_0000094 ! Livermore solver
-relationship: KISAO_0000359 KISAO_0000071 ! LSODE
-property_value: altLabel "Livermore solver for ordinary differential equations given in implicit form, with block-tridiagonal Jacobian treatment" xsd:string {comment="EXACT"}
-property_value: definition "LSOIBT solves linearly implicit systems in which the matrices involved are all assumed to be block-tridiagonal. Linear systems are solved by the LU method." xsd:string
+is_a: kisao:KISAO_0000094 ! Livermore solver
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000071 ! LSODE
 property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
+property_value: skos:altLabel "Livermore solver for ordinary differential equations given in implicit form, with block-tridiagonal Jacobian treatment" xsd:string {comment="EXACT"}
+property_value: skos:definition "LSOIBT solves linearly implicit systems in which the matrices involved are all assumed to be block-tridiagonal. Linear systems are solved by the LU method." xsd:string
 
 [Term]
-id: KISAO_0000233
+id: kisao:KISAO_0000233
 name: LSODES
-is_a: KISAO_0000094 ! Livermore solver
-relationship: KISAO_0000359 KISAO_0000071 ! LSODE
-property_value: altLabel "Livermore solver for ordinary differential equations with general sparse Jacobian matrix" xsd:string {comment="EXACT"}
-property_value: definition "LSODES solves systems dy/dt = f and in the stiff case treats the Jacobian matrix in general sparse form. It determines the sparsity structure on its own, or optionally accepts this information from the user. It then uses parts of the Yale Sparse Matrix Package (YSMP) to solve the linear systems that arise, by a sparse (direct) LU factorization/backsolve method." xsd:string
+is_a: kisao:KISAO_0000094 ! Livermore solver
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000071 ! LSODE
 property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
+property_value: skos:altLabel "Livermore solver for ordinary differential equations with general sparse Jacobian matrix" xsd:string {comment="EXACT"}
+property_value: skos:definition "LSODES solves systems dy/dt = f and in the stiff case treats the Jacobian matrix in general sparse form. It determines the sparsity structure on its own, or optionally accepts this information from the user. It then uses parts of the Yale Sparse Matrix Package (YSMP) to solve the linear systems that arise, by a sparse (direct) LU factorization/backsolve method." xsd:string
 
 [Term]
-id: KISAO_0000234
+id: kisao:KISAO_0000234
 name: LSODKR
-is_a: KISAO_0000094 ! Livermore solver
-relationship: KISAO_0000359 KISAO_0000071 ! LSODE
-relationship: KISAO_0000359 KISAO_0000093 ! LSODPK
-relationship: KISAO_0000360 KISAO_0000354 ! Krylov subspace projection method
-property_value: altLabel "Livermore solver for ordinary differential equations, with preconditioned Krylov iteration methods for the Newton correction linear systems, and with root finding." xsd:string {comment="EXACT"}
-property_value: definition "LSODKR is an initial value ODE solver for stiff and nonstiff systems. It is a variant of the LSODPK [http://identifiers.org/biomodels.kisao/KISAO_0000093] and LSODE [http://identifiers.org/biomodels.kisao/KISAO_0000071] solvers, intended mainly for large stiff systems. The main differences between LSODKR and LSODE [http://identifiers.org/biomodels.kisao/KISAO_0000071] are the following: a) for stiff systems, LSODKR uses a corrector iteration composed of Newton iteration and one of four preconditioned Krylov subspace iteration methods. The user must supply routines for the preconditioning operations, b) within the corrector iteration, LSODKR does automatic switching between functional (fixpoint) iteration and modified Newton iteration, c) LSODKR includes the ability to find roots of given functions of the solution during the integration." xsd:string
+is_a: kisao:KISAO_0000094 ! Livermore solver
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000071 ! LSODE
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000093 ! LSODPK
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000354 ! Krylov subspace projection method
 property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
+property_value: skos:altLabel "Livermore solver for ordinary differential equations, with preconditioned Krylov iteration methods for the Newton correction linear systems, and with root finding." xsd:string {comment="EXACT"}
+property_value: skos:definition "LSODKR is an initial value ODE solver for stiff and nonstiff systems. It is a variant of the LSODPK [http://identifiers.org/biomodels.kisao/KISAO_0000093] and LSODE [http://identifiers.org/biomodels.kisao/KISAO_0000071] solvers, intended mainly for large stiff systems. The main differences between LSODKR and LSODE [http://identifiers.org/biomodels.kisao/KISAO_0000071] are the following: a) for stiff systems, LSODKR uses a corrector iteration composed of Newton iteration and one of four preconditioned Krylov subspace iteration methods. The user must supply routines for the preconditioning operations, b) within the corrector iteration, LSODKR does automatic switching between functional (fixpoint) iteration and modified Newton iteration, c) LSODKR includes the ability to find roots of given functions of the solution during the integration." xsd:string
+
+[Term]
+id: kisao:KISAO_0000235
+name: type of solution
+is_a: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A characteristic describing the type of the solution produced by the method, specifically whether it is exact or approximate." xsd:string
+
+[Term]
+id: kisao:KISAO_0000236
+name: exact solution
+is_a: kisao:KISAO_0000235 ! type of solution
+disjoint_from: kisao:KISAO_0000237 ! approximate solution
+property_value: skos:definition "Algorithm, possessing this characteristic, provides an exact solution to the initial problem." xsd:string
 
 [Term]
-id: KISAO_0000241
+id: kisao:KISAO_0000237
+name: approximate solution
+is_a: kisao:KISAO_0000235 ! type of solution
+property_value: skos:definition "Approximation algorithms are algorithms used to find approximate solutions to optimization problems. Approximation algorithms are often associated with NP-hard problems; since it is unlikely that there can ever be efficient polynomial time exact algorithms solving NP-hard problems, one settles for polynomial time sub-optimal solutions. Unlike heuristics, which usually only find reasonably good solutions reasonably fast, one wants provable solution quality and provable run time bounds. Ideally, the approximation is optimal up to a small constant factor (for instance within 5% of the optimal solution). Approximation algorithms are increasingly being used for problems where exact polynomial-time algorithms are known but are too expensive due to the input size." xsd:string
+
+[Term]
+id: kisao:KISAO_0000238
+name: type of method
+is_a: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A characteristic describing the way the method finds a solution, specifically whether it solves an equation involving only the current state of the system (explicit) or both the current and the later one (implicit). " xsd:string
+
+[Term]
+id: kisao:KISAO_0000239
+name: explicit method type
+is_a: kisao:KISAO_0000238 ! type of method
+disjoint_from: kisao:KISAO_0000240 ! implicit method type
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "Explicit methods calculate the state of a system at a later time from the state of the system at the current time. Mathematically, if Y(t) is the current system state and Y((t+delta t) is the state at the later time (delta t is a small time step), then, for an explicit method Y(t+delta t) = F(Y(t)), to find Y(t+delta t)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000240
+name: implicit method type
+is_a: kisao:KISAO_0000238 ! type of method
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "Implicit methods find a solution by solving an equation involving both the current state of the system and the later one. Mathematically, if Y(t) is the current system state and Y((t+delta t) is the state at the later time (delta t is a small time step), then, for an implicit method one solves an equation G(Y(t), Y(t+delta t))=0, to find Y(t+delta t)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000241
 name: Gillespie-like method
-is_a: KISAO_0000319 ! Monte Carlo method
-disjoint_from: KISAO_0000274 ! first-passage Monte Carlo algorithm
-property_value: definition "Stochastic simulation algorithm using an approach alike the one described in Gillespie's papers of 1976 and 1977." xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000319 ! Monte Carlo method
+disjoint_from: kisao:KISAO_0000274 ! first-passage Monte Carlo algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000105 ! discrete variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000107 ! progression with adaptive time step
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Stochastic simulation algorithm using an approach alike the one described in Gillespie's papers of 1976 and 1977." xsd:string
+
+[Term]
+id: kisao:KISAO_0000242
+name: error control parameter
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+disjoint_from: kisao:KISAO_0000243 ! method switching control parameter
+disjoint_from: kisao:KISAO_0000243 ! method switching control parameter
+disjoint_from: kisao:KISAO_0000243 ! method switching control parameter
+disjoint_from: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Parameter controlling method accuracy." xsd:string
+
+[Term]
+id: kisao:KISAO_0000243
+name: method switching control parameter
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+disjoint_from: kisao:KISAO_0000420 ! number of partial least squares components
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Parameters describing threshold conditions for algorithms that switch between different methods." xsd:string
+
+[Term]
+id: kisao:KISAO_0000244
+name: granularity control parameter
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Parameter controlling granularity." xsd:string
+
+[Term]
+id: kisao:KISAO_0000248
+name: tau-leaping delta
+is_a: kisao:KISAO_0000252 ! partitioning control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000045 {all_only="true"} ! implicit tau-leaping method
+property_value: skos:definition "Tau-leaping delta specifies how close two symmetric transition rates must be before we classify them as in partial-equilibrium. Only applies to the implicit tau routine [http://identifiers.org/biomodels.kisao/KISAO_0000045]." xsd:string
+
+[Term]
+id: kisao:KISAO_0000249
+name: critical firing threshold
+is_a: kisao:KISAO_0000252 ! partitioning control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000084 {all_only="true"} ! nonnegative Poisson tau-leaping method
+property_value: skos:altLabel "nonnegative tau-leaping second control parameter" xsd:string {comment="EXACT"}
+property_value: skos:definition "The 'nonnegative Poisson tau-leaping method' [http://identifiers.org/biomodels.kisao/KISAO_0000084] is based on the fact that negative populations typically arise from multiple firings of reactions that are only a few firings away from consuming all the molecules of one of their reactants. To focus on those reaction channels, the modified tau-leaping algorithm introduces a second control parameter nc, a positive integer that is usually set somewhere between 5 and 20. Any reaction channel with a positive propensity function that is currently within nc firings of exhausting one of its reactants is then classified as a critical reaction. The modified algorithm chooses tau in such a way that no more than one firing of all the critical reactions can occur during the leap." xsd:string
+
+[Term]
+id: kisao:KISAO_0000252
+name: partitioning control parameter
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "Parameter describing partitioning of the system." xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+
+[Term]
+id: kisao:KISAO_0000253
+name: coarse-graining factor
+is_a: kisao:KISAO_0000244 ! granularity control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000074 {all_only="true"} ! binomial tau-leaping method
+property_value: seeAlso "http://identifiers.org/pubmed/15638577" xsd:anyURI {comment="Chatterjee A, Vlachos DG, Katsoulakis MA. Binomial distribution based tau-leap accelerated stochastic simulation. J Chem Phys. 2005;122(2):024112."}
+property_value: skos:definition "The time in each Monte-Carlo iteration of 'binomial tau-leaping method' [http://identifiers.org/biomodels.kisao/KISAO_0000074] is updated with the time increments tau=f/(a1+a2+...+aM). Here 1/(a1+a2+...+aM) is the averaged microscopic increment of the SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] and f is a coarse-graining factor, controlling the speed-up." xsd:string
+
+[Term]
+id: kisao:KISAO_0000254
+name: Brownian diffusion accuracy
+is_a: kisao:KISAO_0000242 ! error control parameter
+disjoint_from: kisao:KISAO_0000325 ! minimum fast/discrete reaction occurrences number
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000057 {all_only="true"} ! Brownian diffusion Smoluchowski method
+property_value: kisao:isImplementedIn "Smoldyn" xsd:string
+property_value: skos:definition "Accuracy code of 'Brownian diffusion Smoluchowski method' [http://identifiers.org/biomodels.kisao/KISAO_0000057], which sets which neighbouring boxes are checked for potential bi-molecular reactions. Consider the reaction A + B -> C and suppose that A and B are within a binding radius of each other. This reaction will always be performed if A and B are in the same virtual box. If accuracy is set to at least 3, then it will also occur if A and B are in nearest-neighbour virtual boxes. If it is at least 7, then the reaction will happen if they are in nearest-neighbour boxes that are separated by periodic boundary conditions. And if it is 9 or 10, then all edge and corner boxes are checked for reactions, which means that no potential reactions are overlooked." xsd:string
+
+[Term]
+id: kisao:KISAO_0000255
+name: molecules per virtual box
+is_a: kisao:KISAO_0000260 ! virtual box size
+disjoint_from: kisao:KISAO_0000256 ! virtual box side length
+property_value: kisao:isImplementedIn "Smoldyn" xsd:string
+property_value: skos:definition "Target molecules per virtual box is a parameter of 'Brownian diffusion Smoluchowski method' [http://identifiers.org/biomodels.kisao/KISAO_0000057], which sets the box sizes so that the average number of molecules per box, at simulation initiation, is close to the requested number." xsd:string
 
 [Term]
-id: KISAO_0000261
+id: kisao:KISAO_0000256
+name: virtual box side length
+is_a: kisao:KISAO_0000260 ! virtual box size
+property_value: kisao:isImplementedIn "Smoldyn" xsd:string
+property_value: skos:definition "The 'virtual box side length' is a parameter of 'Brownian diffusion Smoluchowski method' [http://identifiers.org/biomodels.kisao/KISAO_0000057]. It requests the length of one side of a box." xsd:string
+
+[Term]
+id: kisao:KISAO_0000257
+name: surface-bound epsilon
+is_a: kisao:KISAO_0000252 ! partitioning control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000057 {all_only="true"} ! Brownian diffusion Smoluchowski method
+property_value: skos:definition "A parameter of 'Brownian diffusion Smoluchowski method' [http://identifiers.org/biomodels.kisao/KISAO_0000057]. Molecules that are bound to a surface are given locations that are extremely close to that surface. However, this position does not need to be exactly at the surface, and in fact it usually cannot be exactly at the surface due to round-off error. The tolerance for how  far a surface-bound molecule is allowed to be away from the surface can be set with the epsilon statement." xsd:string
+
+[Term]
+id: kisao:KISAO_0000258
+name: neighbour distance
+is_a: kisao:KISAO_0000252 ! partitioning control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000057 {all_only="true"} ! Brownian diffusion Smoluchowski method
+property_value: skos:definition "A parameter of 'Brownian diffusion Smoluchowski method' [http://identifiers.org/biomodels.kisao/KISAO_0000057]. When a surface-bound molecule diffuses off of one surface panel, it can sometimes diffuse onto the neighbouring surface tile. It does so only if the neighbouring panel is declared to be a neighbour and also the neighbour is within a distance that is set with the neighbour distance statement." xsd:string
+
+[Term]
+id: kisao:KISAO_0000260
+name: virtual box size
+is_a: kisao:KISAO_0000252 ! partitioning control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000057 {all_only="true"} ! Brownian diffusion Smoluchowski method
+property_value: skos:definition "Target size of virtual boxes for 'Brownian diffusion Smoluchowski method' [http://identifiers.org/biomodels.kisao/KISAO_0000057]." xsd:string
+
+[Term]
+id: kisao:KISAO_0000261
 name: Euler method
-is_a: KISAO_0000377 ! one-step method
-property_value: definition "The Euler method, named after Leonhard Euler, is a first-order numerical procedure for solving ordinary differential equations (ODEs) with a given initial value." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "ByoDyn" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+is_a: kisao:KISAO_0000377 ! one-step method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000376 ! linearity of equation
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "ByoDyn" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
 property_value: seeAlso "http://identifiers.org/isbn/052143064X" xsd:anyURI {comment="Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical Recipes in Fortran 77. Cambridge University Press (2001)."}
+property_value: skos:definition "The Euler method, named after Leonhard Euler, is a first-order numerical procedure for solving ordinary differential equations (ODEs) with a given initial value." xsd:string
 
 [Term]
-id: KISAO_0000263
+id: kisao:KISAO_0000263
 name: NFSim agent-based simulation method
-is_a: KISAO_0000017 ! multi-state agent-based simulation method
-disjoint_from: KISAO_0000362 ! implicit-state Doob-Gillespie algorithm
-relationship: KISAO_0000361 KISAO_0000029 ! Gillespie direct algorithm
-property_value: definition "A generalization a rule-based version of 'Gillespie's direct method' (SSA) [http://identifiers.org/biomodels.kisao/KISAO_0000029]. The method is guaranteed to produce the same results as the exact SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] by cycling over three primary steps. First, NFsim calculates the probability or propensity for each rule to take effect given the current molecular states. Second, it samples the time to the next reaction event and selects the corresponding reaction rule. Finally, NFsim executes the selected reaction by applying the rule and updating the molecular agents accordingly." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/bionetgen" xsd:anyURI {comment="NFSim"}
+is_a: kisao:KISAO_0000017 ! multi-state agent-based simulation method
+disjoint_from: kisao:KISAO_0000362 ! implicit-state Doob-Gillespie algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000029 ! Gillespie direct algorithm
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/bionetgen" xsd:anyURI {comment="NFSim"}
 property_value: seeAlso "http://identifiers.org/doi/10.1038/nmeth.1546" xsd:anyURI {comment="Sneddon MW, Faeder JR and Emonet T. Efficient modelling, simulation and coarse-graining of biological complexity with NFsim. Nature Methods (2011) 8(2):177-83."}
+property_value: skos:definition "A generalization a rule-based version of 'Gillespie's direct method' (SSA) [http://identifiers.org/biomodels.kisao/KISAO_0000029]. The method is guaranteed to produce the same results as the exact SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] by cycling over three primary steps. First, NFsim calculates the probability or propensity for each rule to take effect given the current molecular states. Second, it samples the time to the next reaction event and selects the corresponding reaction rule. Finally, NFsim executes the selected reaction by applying the rule and updating the molecular agents accordingly." xsd:string
 
 [Term]
-id: KISAO_0000264
+id: kisao:KISAO_0000264
 name: cellular automata update method
-is_a: KISAO_0000363 ! rule-based simulation method
-property_value: altLabel "CA" xsd:string {comment="EXACT"}
-property_value: altLabel "cellular automata" xsd:string {comment="EXACT"}
-property_value: altLabel "cellular spaces" xsd:string {comment="EXACT"}
-property_value: altLabel "cellular structures" xsd:string {comment="EXACT"}
-property_value: altLabel "homogeneous structures" xsd:string {comment="EXACT"}
-property_value: altLabel "iterative arrays" xsd:string {comment="EXACT"}
-property_value: altLabel "tessellation automata" xsd:string {comment="EXACT"}
-property_value: altLabel "tessellation structures" xsd:string {comment="EXACT"}
-property_value: definition "Cellular automata are mathematical idealizations of physical systems in which space and time are discrete, and physical quantities take on a finite set of discrete values. A cellular automaton consists of a regular uniform lattice (or ''array''), usually infinite in extent, with a discrete variable at each site (''cell''). A cellular automaton evolves in discrete time steps, with the value of the variable at one site being affected by the values of variables at sites in its ''neighbourhood'' on the previous time step. The neighbourhood of a site is typically taken to be the site itself and all immediately adjacent sites. The variables at each site are updated simultaneously (''synchronously''), based on the values of the variables in their neighbourhood at the preceding time step, and according to a definite set of ''local rules''." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000363 ! rule-based simulation method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000102 ! spatial description
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1103/RevModPhys.55.601" xsd:anyURI {comment="Wolfram, Stephen (1983) Statistical mechanics of cellular automata. Reviews of Modern Physics 55 (3): 601-644."}
-
-[Term]
-id: KISAO_0000273
+property_value: skos:altLabel "CA" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "cellular automata" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "cellular spaces" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "cellular structures" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "homogeneous structures" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "iterative arrays" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "tessellation automata" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "tessellation structures" xsd:string {comment="EXACT"}
+property_value: skos:definition "Cellular automata are mathematical idealizations of physical systems in which space and time are discrete, and physical quantities take on a finite set of discrete values. A cellular automaton consists of a regular uniform lattice (or ''array''), usually infinite in extent, with a discrete variable at each site (''cell''). A cellular automaton evolves in discrete time steps, with the value of the variable at one site being affected by the values of variables at sites in its ''neighbourhood'' on the previous time step. The neighbourhood of a site is typically taken to be the site itself and all immediately adjacent sites. The variables at each site are updated simultaneously (''synchronously''), based on the values of the variables in their neighbourhood at the preceding time step, and according to a definite set of ''local rules''." xsd:string
+
+[Term]
+id: kisao:KISAO_0000273
 name: hard-particle molecular dynamics
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: definition "A collision-driven molecular dynamics algorithm for a system of non-spherical particles." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000102 ! spatial description
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000107 ! progression with adaptive time step
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1016/j.jcp.2004.08.014" xsd:anyURI {comment="Aleksandar Donev, Salvatore Torquato, Frank H. Stillinger, Neighbor list collision-driven molecular dynamics simulation for nonspherical hard particles. I. Algorithmic details, Journal of Computational Physics, v.202 n.2, p.737-764, 20 January 2005"}
+property_value: skos:definition "A collision-driven molecular dynamics algorithm for a system of non-spherical particles." xsd:string
 
 [Term]
-id: KISAO_0000274
+id: kisao:KISAO_0000274
 name: first-passage Monte Carlo algorithm
-is_a: KISAO_0000319 ! Monte Carlo method
-property_value: altLabel "AED diffusion kinetic Monte Carlo method" xsd:string {comment="EXACT"}
-property_value: altLabel "AED DKMC" xsd:string {comment="EXACT"}
-property_value: altLabel "asynchronous event-driven diffusion Monte Carlo" xsd:string {comment="EXACT"}
-property_value: definition "We present a novel Monte Carlo algorithm for N diffusing finite particles that react on collisions. Using the theory of first-passage processes and time dependent Green's functions, we break the difficult N-body problem into independent single- and two-body propagations circumventing numerous diffusion hops used in standard Monte Carlo simulations. The new algorithm is exact, extremely efficient, and applicable to many important physical situations in arbitrary integer dimensions." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000319 ! Monte Carlo method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000102 ! spatial description
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000107 ! progression with adaptive time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1103/PhysRevLett.97.230602" xsd:anyURI {comment="T. Oppelstrup, V. V. Bulatov, G. H. Gilmer, M. H. Kalos, and B. Sadigh. First-passage Monte- Carlo algorithm: Diffusion without all the hops. Physical Review Letters, 97(23):230602, 2006."}
+property_value: skos:altLabel "AED diffusion kinetic Monte Carlo method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "AED DKMC" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "asynchronous event-driven diffusion Monte Carlo" xsd:string {comment="EXACT"}
+property_value: skos:definition "We present a novel Monte Carlo algorithm for N diffusing finite particles that react on collisions. Using the theory of first-passage processes and time dependent Green's functions, we break the difficult N-body problem into independent single- and two-body propagations circumventing numerous diffusion hops used in standard Monte Carlo simulations. The new algorithm is exact, extremely efficient, and applicable to many important physical situations in arbitrary integer dimensions." xsd:string
 
 [Term]
-id: KISAO_0000276
+id: kisao:KISAO_0000276
 name: Gill method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: altLabel "Gill's method" xsd:string {comment="EXACT"}
-property_value: altLabel "Runge-Kutta-Gill method" xsd:string {comment="EXACT"}
-property_value: definition "Gill's fourth order method is a Runge-Kutta method for approximating the solution of the initial value problem y'(x) = f(x,y);  y(x0) = y0 which evaluates the integrand,f(x,y), four times per step. This method is a fourth order procedure for which Richardson extrapolation can be used." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000239 ! explicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1017/S0305004100026414" xsd:anyURI {comment="Gill, S. 1951. A process for the step-by-step integration of differential equations in an automatic digital computing machine. Proc. Cambridge Philos. Soc., 47, pp 96-108."}
+property_value: skos:altLabel "Gill's method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Runge-Kutta-Gill method" xsd:string {comment="EXACT"}
+property_value: skos:definition "Gill's fourth order method is a Runge-Kutta method for approximating the solution of the initial value problem y'(x) = f(x,y);  y(x0) = y0 which evaluates the integrand,f(x,y), four times per step. This method is a fourth order procedure for which Richardson extrapolation can be used." xsd:string
 
 [Term]
-id: KISAO_0000278
+id: kisao:KISAO_0000278
 name: Metropolis Monte Carlo algorithm
-is_a: KISAO_0000319 ! Monte Carlo method
-property_value: altLabel "Metropolis algorithm" xsd:string {comment="EXACT"}
-property_value: altLabel "Metropolis-Hastings algorithm" xsd:string {comment="EXACT"}
-property_value: definition "A general method, suitable for fast computing machines, for investigating such properties as equations of state for substances consisting of interacting individual molecules is described. The method consists of a modified Monte Carlo integration [http://identifiers.org/biomodels.kisao/KISAO_0000051] over configuration space." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "CompuCell3D" xsd:string
+is_a: kisao:KISAO_0000319 ! Monte Carlo method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000102 ! spatial description
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "CompuCell3D" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1699114" xsd:anyURI {comment="Metropolis, N.; Rosenbluth, A.W.; Rosenbluth, M.N.; Teller, A.H.; Teller, E. (1953). Equations of State Calculations by Fast Computing Machines. Journal of Chemical Physics 21 (6): 1087-1092."}
+property_value: skos:altLabel "Metropolis algorithm" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Metropolis-Hastings algorithm" xsd:string {comment="EXACT"}
+property_value: skos:definition "A general method, suitable for fast computing machines, for investigating such properties as equations of state for substances consisting of interacting individual molecules is described. The method consists of a modified Monte Carlo integration [http://identifiers.org/biomodels.kisao/KISAO_0000051] over configuration space." xsd:string
 
 [Term]
-id: KISAO_0000279
+id: kisao:KISAO_0000279
 name: Adams-Bashforth method
-is_a: KISAO_0000289 ! Adams method
-disjoint_from: KISAO_0000280 ! Adams-Moulton method
-property_value: altLabel "explicit Adams method" xsd:string {comment="EXACT"}
-property_value: definition "Given an initial value problem: y' = f(x,y),  y(x0) = y0 together with additional starting values y1 = y(x0 + h), . . . , yk-1 = y(x0 + (k-1) h) the k-step Adams-Bashforth method is an explicit linear multistep method that approximates the solution, y(x) at x = x0+kh, of the initial value problem by yk = yk - 1 + h * ( a0 f(xk - 1,yk - 1) + a1 f(xk - 2,yk - 2) + . . . + ak - 1 f(x0,y0) ), where a0, a1, . . . , ak - 1 are constants." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000289 ! Adams method
+disjoint_from: kisao:KISAO_0000280 ! Adams-Moulton method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000239 ! explicit method type
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+property_value: skos:altLabel "explicit Adams method" xsd:string {comment="EXACT"}
+property_value: skos:definition "Given an initial value problem: y' = f(x,y),  y(x0) = y0 together with additional starting values y1 = y(x0 + h), . . . , yk-1 = y(x0 + (k-1) h) the k-step Adams-Bashforth method is an explicit linear multistep method that approximates the solution, y(x) at x = x0+kh, of the initial value problem by yk = yk - 1 + h * ( a0 f(xk - 1,yk - 1) + a1 f(xk - 2,yk - 2) + . . . + ak - 1 f(x0,y0) ), where a0, a1, . . . , ak - 1 are constants." xsd:string
 
 [Term]
-id: KISAO_0000280
+id: kisao:KISAO_0000280
 name: Adams-Moulton method
-is_a: KISAO_0000289 ! Adams method
-property_value: altLabel "implicit Adams method" xsd:string {comment="EXACT"}
-property_value: definition "The (k-1)-step Adams-Moulton method is an implicit linear multistep method that iteratively approximates the solution, y(x) at x = x0+kh, of the initial value problem by yk = yk - 1 + h * ( b0 f(xk,yk) + b1 f(xk - 1,yk - 1) + . . . + bk - 1 f(x1,y1) ), where b1, . . . , bk - 1 are constants." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+is_a: kisao:KISAO_0000289 ! Adams method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
 property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+property_value: skos:altLabel "implicit Adams method" xsd:string {comment="EXACT"}
+property_value: skos:definition "The (k-1)-step Adams-Moulton method is an implicit linear multistep method that iteratively approximates the solution, y(x) at x = x0+kh, of the initial value problem by yk = yk - 1 + h * ( b0 f(xk,yk) + b1 f(xk - 1,yk - 1) + . . . + bk - 1 f(x1,y1) ), where b1, . . . , bk - 1 are constants." xsd:string
 
 [Term]
-id: KISAO_0000281
+id: kisao:KISAO_0000281
 name: multistep method
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: altLabel "multi-value method" xsd:string {comment="EXACT"}
-property_value: definition "A numerical method for differential equations which is based on several values of the solution." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+property_value: skos:altLabel "multi-value method" xsd:string {comment="EXACT"}
+property_value: skos:definition "A numerical method for differential equations which is based on several values of the solution." xsd:string
 
 [Term]
-id: KISAO_0000282
+id: kisao:KISAO_0000282
 name: KINSOL
-is_a: KISAO_0000408 ! Newton-type method
-disjoint_from: KISAO_0000409 ! ordinary Newton method
-disjoint_from: KISAO_0000412 ! inexact Newton method
-relationship: KISAO_0000360 KISAO_0000354 ! Krylov subspace projection method
-property_value: altLabel "FKINSOL" xsd:string {comment="RELATED"}
-property_value: altLabel "Newton-Krylov solver for nonlinear algebraic systems" xsd:string {comment="RELATED"}
-property_value: altLabel "NKSOL" xsd:string {comment="RELATED"}
-property_value: definition "KINSOL solves algebraic systems in real N-space, written as F(u)=0,  F:RN->RN, given an initial guess u0. The basic method is either a modified or an inexact Newton iteration [http://identifiers.org/biomodels.kisao/KISAO_0000408]. The linear systems that arise are solved with either a direct (dense or banded) solver (serial version only), or one of the Krylov iterative solvers [http://identifiers.org/biomodels.kisao/KISAO_0000354]. In the Krylov case, the user can (optionally) supply a right preconditioner." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "SUNDIALS" xsd:string
+is_a: kisao:KISAO_0000408 ! Newton-type method
+disjoint_from: kisao:KISAO_0000409 ! ordinary Newton method
+disjoint_from: kisao:KISAO_0000412 ! inexact Newton method
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000354 ! Krylov subspace projection method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "SUNDIALS" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0911026" xsd:anyURI {comment="BROWN, P. N. AND SAAD, Y. 1990. Hybrid Krylov methods for nonlinear systems of equations. SIAM  J. Sci. Stat. Comput. 11, 450-481."}
 property_value: seeAlso "http://identifiers.org/doi/10.1145/1089014.1089020" xsd:anyURI {comment="Hindmarsh, A. C., et al., SUNDIALS: Suite of Nonlinear and Differential/Algebraic Equation Solvers, ACM Trans. Math. Softw., 31:363-396, 2005."}
 property_value: seeAlso "http://identifiers.org/doi/10.4249/scholarpedia.2860" xsd:anyURI {comment="Alan C. Hindmarsh and Radu Serban (2007) Sundails equation solvers, Scholarpedia, 2(3):2860."}
+property_value: skos:altLabel "FKINSOL" xsd:string {comment="RELATED"}
+property_value: skos:altLabel "Newton-Krylov solver for nonlinear algebraic systems" xsd:string {comment="RELATED"}
+property_value: skos:altLabel "NKSOL" xsd:string {comment="RELATED"}
+property_value: skos:definition "KINSOL solves algebraic systems in real N-space, written as F(u)=0,  F:RN->RN, given an initial guess u0. The basic method is either a modified or an inexact Newton iteration [http://identifiers.org/biomodels.kisao/KISAO_0000408]. The linear systems that arise are solved with either a direct (dense or banded) solver (serial version only), or one of the Krylov iterative solvers [http://identifiers.org/biomodels.kisao/KISAO_0000354]. In the Krylov case, the user can (optionally) supply a right preconditioner." xsd:string
 
 [Term]
-id: KISAO_0000283
+id: kisao:KISAO_0000283
 name: IDA {comment="Alan C. Hindmarsh and Radu Serban (2007) Sundails equation solvers, Scholarpedia, 2(3):2860."}
-is_a: KISAO_0000432 ! IDA-like method
-relationship: KISAO_0000359 KISAO_0000355 ! DASPK
-relationship: KISAO_0000360 KISAO_0000288 ! backward differentiation formula
-relationship: KISAO_0000360 KISAO_0000354 ! Krylov subspace projection method
-relationship: KISAO_0000360 KISAO_0000386 ! scaled preconditioned generalized minimal residual method
-property_value: altLabel "implicit differential-algebraic solver" xsd:string {comment="EXACT"}
-property_value: altLabel "solver for differential-algebraic equation systems" xsd:string {comment="RELATED"}
-property_value: definition "IDA solves real differential-algebraic systems in N-space, in the general form F(t,y,y')=0,  y(t0)=y0,  y'(t0)=y'0. At each step, a Newton iteration [http://identifiers.org/biomodels.kisao/KISAO_0000408] leads to linear systems Jx=b, which are solved by one of five methods - two direct (dense or band; serial version only) and three Krylov [http://identifiers.org/biomodels.kisao/KISAO_0000354] (GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000353], BiCGStab [http://identifiers.org/biomodels.kisao/KISAO_0000392], or TFQMR [http://identifiers.org/biomodels.kisao/KISAO_0000396]).\nIDA is written in C, but derived from the package DASPK [http://identifiers.org/biomodels.kisao/KISAO_0000355] which is written in Fortran." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/opencor" xsd:anyURI {comment="OpenCOR"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
-property_value: isImplementedIn "SUNDIALS" xsd:string
+is_a: kisao:KISAO_0000432 ! IDA-like method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000373 ! differential-algebraic equation problem
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000477 {maxCardinality="1"} ! linear solver
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000479 {maxCardinality="1"} ! upper half-bandwidth
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000480 {maxCardinality="1"} ! lower half-bandwidth
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000481 {maxCardinality="1"} ! interpolate solution
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000355 ! DASPK
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000288 ! backward differentiation formula
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000354 ! Krylov subspace projection method
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000386 ! scaled preconditioned generalized minimal residual method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/opencor" xsd:anyURI {comment="OpenCOR"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: kisao:isImplementedIn "SUNDIALS" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0915088" xsd:anyURI {comment="BROWN, P. N., HINDMARSH, A. C., AND PETZOLD, L. R. 1994. Using Krylov methods in the solution of large-scale differential-algebraic systems. SIAM J. Sci. Comput. 15, 1467-1488."}
 property_value: seeAlso "http://identifiers.org/doi/10.1145/1089014.1089020" xsd:anyURI {comment="Hindmarsh, A. C., et al., SUNDIALS: Suite of Nonlinear and Differential/Algebraic Equation Solvers, ACM Trans. Math. Softw., 31:363-396, 2005."}
 property_value: seeAlso "http://identifiers.org/doi/10.4249/scholarpedia.2860" xsd:anyURI {comment="Alan C. Hindmarsh and Radu Serban (2007) Sundails equation solvers, Scholarpedia, 2(3):2860."}
+property_value: skos:altLabel "implicit differential-algebraic solver" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "solver for differential-algebraic equation systems" xsd:string {comment="RELATED"}
+property_value: skos:definition "IDA solves real differential-algebraic systems in N-space, in the general form F(t,y,y')=0,  y(t0)=y0,  y'(t0)=y'0. At each step, a Newton iteration [http://identifiers.org/biomodels.kisao/KISAO_0000408] leads to linear systems Jx=b, which are solved by one of five methods - two direct (dense or band; serial version only) and three Krylov [http://identifiers.org/biomodels.kisao/KISAO_0000354] (GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000353], BiCGStab [http://identifiers.org/biomodels.kisao/KISAO_0000392], or TFQMR [http://identifiers.org/biomodels.kisao/KISAO_0000396]).\nIDA is written in C, but derived from the package DASPK [http://identifiers.org/biomodels.kisao/KISAO_0000355] which is written in Fortran." xsd:string
 
 [Term]
-id: KISAO_0000285
+id: kisao:KISAO_0000285
 name: finite volume method
-is_a: KISAO_0000369 ! partial differential equation discretization method
-disjoint_from: KISAO_0000307 ! finite difference method
-property_value: altLabel "FVM" xsd:string {comment="EXACT"}
-property_value: definition "The finite volume method is a method for representing and evaluating partial differential equations in the form of algebraic equations, which attempts to emulate continuous conservation laws of physics." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+is_a: kisao:KISAO_0000369 ! partial differential equation discretization method
+disjoint_from: kisao:KISAO_0000307 ! finite difference method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000346 ! mesh-based geometry handling
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
 property_value: seeAlso "http://identifiers.org/isbn/0898715342" xsd:anyURI {comment="Y. Saad. 2003. Iterative Methods for Sparse Linear Systems (2nd ed.). Soc. for Industrial and Applied Math., Philadelphia, PA, USA."}
+property_value: skos:altLabel "FVM" xsd:string {comment="EXACT"}
+property_value: skos:definition "The finite volume method is a method for representing and evaluating partial differential equations in the form of algebraic equations, which attempts to emulate continuous conservation laws of physics." xsd:string
 
 [Term]
-id: KISAO_0000286
+id: kisao:KISAO_0000286
 name: Euler-Maruyama method
-is_a: KISAO_0000377 ! one-step method
-relationship: KISAO_0000361 KISAO_0000261 ! Euler method
-property_value: altLabel "stochastic Euler scheme" xsd:string {comment="EXACT"}
-property_value: definition "The Euler-Maruyama method is a method for the approximate numerical solution of a stochastic differential equation, which truncates the Ito and Stratonovich Taylor series of the exact solution after the first order stochastic terms. This converges to the Ito solution with strong global order accuracy 1/2 or weak global order accuracy 1. It is a simple generalization of the Euler method [http://identifiers.org/biomodels.kisao/KISAO_0000261] for ordinary differential equations to stochastic differential equations." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000697 ! SDE solver
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000483 ! step size
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000261 ! Euler method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1098/rspa.2003.1247" xsd:anyURI {comment="Burrage, K., Burrage, P.M. and Tian, T. (2004) Numerical methods for strong solutions of stochastic differential equations: an overview. Proceedings of the Royal Society of London Series A: Mathematical, Physical and Engineering Sciences, 460 (2041). pp. 373-402."}
+property_value: skos:altLabel "stochastic Euler scheme" xsd:string {comment="EXACT"}
+property_value: skos:definition "The Euler-Maruyama method is a method for the approximate numerical solution of a stochastic differential equation, which truncates the Ito and Stratonovich Taylor series of the exact solution after the first order stochastic terms. This converges to the Ito solution with strong global order accuracy 1/2 or weak global order accuracy 1. It is a simple generalization of the Euler method [http://identifiers.org/biomodels.kisao/KISAO_0000261] for ordinary differential equations to stochastic differential equations." xsd:string
 
 [Term]
-id: KISAO_0000287
+id: kisao:KISAO_0000287
 name: Milstein method
-is_a: KISAO_0000281 ! multistep method
-disjoint_from: KISAO_0000288 ! backward differentiation formula
-property_value: definition "The Milstein method is a technique for the approximate numerical solution of a stochastic differential equation." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000697 ! SDE solver
+disjoint_from: kisao:KISAO_0000288 ! backward differentiation formula
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/079233213X" xsd:anyURI {comment="Milstein M. G. Numerical Integration of Stochastic Differential Equations (Mathematics and Its Applications) Springer, 2004."}
+property_value: skos:definition "The Milstein method is a technique for the approximate numerical solution of a stochastic differential equation." xsd:string
 
 [Term]
-id: KISAO_0000288
+id: kisao:KISAO_0000288
 name: backward differentiation formula
-is_a: KISAO_0000281 ! multistep method
-disjoint_from: KISAO_0000289 ! Adams method
-property_value: altLabel "BDF" xsd:string {comment="EXACT"}
-property_value: altLabel "Gear method" xsd:string {comment="EXACT"}
-property_value: altLabel "Gear's method" xsd:string {comment="EXACT"}
-property_value: definition "The backward differentiation formulas (BDF) are implicit multistep methods based on the numerical differentiation of a given function and are wildly used for integration of stiff differential equations." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "ByoDyn" xsd:string
-property_value: isImplementedIn "GSL" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+is_a: kisao:KISAO_0000281 ! multistep method
+disjoint_from: kisao:KISAO_0000289 ! Adams method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000376 ! linearity of equation
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "ByoDyn" xsd:string
+property_value: kisao:isImplementedIn "GSL" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
 property_value: seeAlso "http://identifiers.org/isbn/0136266061" xsd:anyURI {comment="C. William Gear. 1971. Numerical Initial Value Problems in Ordinary Differential Equations. Prentice Hall PTR, Upper Saddle River, NJ, USA."}
+property_value: skos:altLabel "BDF" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Gear method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Gear's method" xsd:string {comment="EXACT"}
+property_value: skos:definition "The backward differentiation formulas (BDF) are implicit multistep methods based on the numerical differentiation of a given function and are wildly used for integration of stiff differential equations." xsd:string
 
 [Term]
-id: KISAO_0000289
+id: kisao:KISAO_0000289
 name: Adams method
-is_a: KISAO_0000281 ! multistep method
-property_value: definition "Adams' methods are multi-step methods used for the numerical integration of initial value problems in Ordinary Differential Equations (ODE's). Adams' algorithm consists of two parts: firstly, a starting procedure which provides y1, ... , yk-1 ( approximations to the exact solution at the points x0 + h, ... , x0 + (k - 1)h ) and, secondly, a multistep formula to obtain an approximation to the exact solution y(x0 + kh). This is then applied recursively, based on the numerical approximation of k successive steps, to compute y(x0 + (k + 1)h)." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "ByoDyn" xsd:string
+is_a: kisao:KISAO_0000281 ! multistep method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000376 ! linearity of equation
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "ByoDyn" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+property_value: skos:definition "Adams' methods are multi-step methods used for the numerical integration of initial value problems in Ordinary Differential Equations (ODE's). Adams' algorithm consists of two parts: firstly, a starting procedure which provides y1, ... , yk-1 ( approximations to the exact solution at the points x0 + h, ... , x0 + (k - 1)h ) and, secondly, a multistep formula to obtain an approximation to the exact solution y(x0 + kh). This is then applied recursively, based on the numerical approximation of k successive steps, to compute y(x0 + (k + 1)h)." xsd:string
 
 [Term]
-id: KISAO_0000290
+id: kisao:KISAO_0000290
 name: Merson method
-is_a: KISAO_0000302 ! embedded Runge-Kutta method
-disjoint_from: KISAO_0000303 ! Zonneveld method
-property_value: altLabel "KM" xsd:string {comment="EXACT"}
-property_value: altLabel "Kutta-Merson method" xsd:string {comment="EXACT"}
-property_value: altLabel "Merson's method" xsd:string {comment="EXACT"}
-property_value: altLabel "Runge-Kutta-Merson method" xsd:string {comment="EXACT"}
-property_value: definition "A five-stage Runge-Kutta method with fourth-order accuracy." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+is_a: kisao:KISAO_0000302 ! embedded Runge-Kutta method
+disjoint_from: kisao:KISAO_0000303 ! Zonneveld method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
 property_value: seeAlso "http://nla.gov.au/nla.cat-vn870866" xsd:anyURI {comment="R.H. Merson, An operational method for the study of integration processes, in: Proceedings of the Symposium on Data Processing, Weapons Research Establishment, Salisbury, Australia, 1957, pp. 110-1-110-25."}
+property_value: skos:altLabel "KM" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Kutta-Merson method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Merson's method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Runge-Kutta-Merson method" xsd:string {comment="EXACT"}
+property_value: skos:definition "A five-stage Runge-Kutta method with fourth-order accuracy." xsd:string
 
 [Term]
-id: KISAO_0000296
+id: kisao:KISAO_0000296
 name: Hammer-Hollingsworth method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: definition "The numerical integration of ordinary differential equations by the use of Gaussian quadrature methods." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "urn:issn:0891-6837" xsd:anyURI {comment="P. C. Hammer & J. W. Hollingsworth, Trapezoidal methods of approximating solutions of differential equations, MTAC, v. 9, 1955, pp. 92-96. MR 17, 302."}
+property_value: skos:definition "The numerical integration of ordinary differential equations by the use of Gaussian quadrature methods." xsd:string
 
 [Term]
-id: KISAO_0000297
+id: kisao:KISAO_0000297
 name: Lobatto method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: altLabel "implicit Runge-Kutta method based on Lobatto quadrature" xsd:string {comment="EXACT"}
-property_value: definition "There are three families of Lobatto methods, called IIIA, IIIB and IIIC. These are named after Rehuel Lobatto. All are implicit Runge-Kutta methods, have order 2s − 2 and they all have c1 = 0 and cs = 1." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "urn:issn:1088-6842(e)" xsd:anyURI {comment="J. C. Butcher, Integration processes based on Radau quadrature formulas, Math. Comp., v. 18, 1964, pp. 233-244."}
+property_value: skos:altLabel "implicit Runge-Kutta method based on Lobatto quadrature" xsd:string {comment="EXACT"}
+property_value: skos:definition "There are three families of Lobatto methods, called IIIA, IIIB and IIIC. These are named after Rehuel Lobatto. All are implicit Runge-Kutta methods, have order 2s − 2 and they all have c1 = 0 and cs = 1." xsd:string
 
 [Term]
-id: KISAO_0000299
+id: kisao:KISAO_0000299
 name: Butcher-Kuntzmann method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: altLabel "Gauss method" xsd:string {comment="EXACT"}
-property_value: definition "From a theoretical point of view, the Butcher-Kuntzmann Runge-Kutta methods belong to the best step-by-step methods for nonstiff problems. These methods integrate first-order initial-value problems by means of formulas based on Gauss-Legendre quadrature, and combine excellent stability features with the property of superconvergence at the step points." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000366 ! symplecticness
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1002/zamm.19660460519" xsd:anyURI {comment="F. Ceschin, J. Kuntzmann, Problèmes différentiels de conditions initiales. Paris 1963. Dunod."}
 property_value: seeAlso "urn:issn:1088-6842(e)" xsd:anyURI {comment="Butcher, J. C. (1964) Implicit Runge-Kutta processes. Math. Comput. 18, 50-64."}
+property_value: skos:altLabel "Gauss method" xsd:string {comment="EXACT"}
+property_value: skos:definition "From a theoretical point of view, the Butcher-Kuntzmann Runge-Kutta methods belong to the best step-by-step methods for nonstiff problems. These methods integrate first-order initial-value problems by means of formulas based on Gauss-Legendre quadrature, and combine excellent stability features with the property of superconvergence at the step points." xsd:string
 
 [Term]
-id: KISAO_0000301
+id: kisao:KISAO_0000301
 name: Heun method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: altLabel "Heun's method" xsd:string {comment="EXACT"}
-property_value: definition "The method is named after Karl L. W. M. Heun and is a numerical procedure for solving ordinary differential equations (ODEs) with a given initial value. It can be seen as extension of the Euler method [http://identifiers.org/biomodels.kisao/KISAO_0000261] into two-stage second-order Runge-Kutta method." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000239 ! explicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+property_value: skos:altLabel "Heun's method" xsd:string {comment="EXACT"}
+property_value: skos:definition "The method is named after Karl L. W. M. Heun and is a numerical procedure for solving ordinary differential equations (ODEs) with a given initial value. It can be seen as extension of the Euler method [http://identifiers.org/biomodels.kisao/KISAO_0000261] into two-stage second-order Runge-Kutta method." xsd:string
 
 [Term]
-id: KISAO_0000302
+id: kisao:KISAO_0000302
 name: embedded Runge-Kutta method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: altLabel "embedded RK" xsd:string {comment="EXACT"}
-property_value: definition "An embedded Runge-Kutta method is a method in which two Runge-Kutta estimates are obtained using the same auxiliary functions ki but with a different linear combination of these functions so that one estimate has an order one greater than the other." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000107 ! progression with adaptive time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000239 ! explicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+property_value: skos:altLabel "embedded RK" xsd:string {comment="EXACT"}
+property_value: skos:definition "An embedded Runge-Kutta method is a method in which two Runge-Kutta estimates are obtained using the same auxiliary functions ki but with a different linear combination of these functions so that one estimate has an order one greater than the other." xsd:string
 
 [Term]
-id: KISAO_0000303
+id: kisao:KISAO_0000303
 name: Zonneveld method
-is_a: KISAO_0000302 ! embedded Runge-Kutta method
-disjoint_from: KISAO_0000305 ! Verner method
-property_value: definition "An embedded Runge-Kutta method [http://identifiers.org/biomodels.kisao/KISAO_0000302] of order 4(3), proposed by J.A. Zonneveld in 1964." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000302 ! embedded Runge-Kutta method
+disjoint_from: kisao:KISAO_0000305 ! Verner method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://trove.nla.gov.au/work/21424455" xsd:anyURI {comment="Zonneveld, J. A (1970). Automatic numerical integration Mathematisch Centrum, Amsterdam"}
+property_value: skos:definition "An embedded Runge-Kutta method [http://identifiers.org/biomodels.kisao/KISAO_0000302] of order 4(3), proposed by J.A. Zonneveld in 1964." xsd:string
 
 [Term]
-id: KISAO_0000304
+id: kisao:KISAO_0000304
 name: Radau method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: altLabel "implicit Runge-Kutta method based on Radau quadrature" xsd:string {comment="EXACT"}
-property_value: definition "Implicit Runge-Kutta methods based on Radau quadrature." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000484 ! maximum order
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000583 ! minimum order
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000584 ! initial order
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
 property_value: seeAlso "urn:issn:1088-6842(e)" xsd:anyURI {comment="J. C. Butcher, Integration processes based on Radau quadrature formulas, Math. Comput., 18(1964), 233-244."}
+property_value: skos:altLabel "implicit Runge-Kutta method based on Radau quadrature" xsd:string {comment="EXACT"}
+property_value: skos:definition "Implicit Runge-Kutta methods based on Radau quadrature." xsd:string
 
 [Term]
-id: KISAO_0000305
+id: kisao:KISAO_0000305
 name: Verner method
-is_a: KISAO_0000302 ! embedded Runge-Kutta method
-property_value: altLabel "Verner's method" xsd:string {comment="EXACT"}
-property_value: definition "The first high order (6(5)) embedded Runge-Kutta formulas that avoid the drawback of giving identically zero error estimates for quadrature problems y' = f(x) were constructed by Verner in 1978." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000302 ! embedded Runge-Kutta method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0728027" xsd:anyURI {comment="J.H. Verner, Some Runge-Kutta formula pairs, SIAM J. Numer. Anal 28 (1991) 496-511"}
+property_value: skos:altLabel "Verner's method" xsd:string {comment="EXACT"}
+property_value: skos:definition "The first high order (6(5)) embedded Runge-Kutta formulas that avoid the drawback of giving identically zero error estimates for quadrature problems y' = f(x) were constructed by Verner in 1978." xsd:string
 
 [Term]
-id: KISAO_0000306
+id: kisao:KISAO_0000306
 name: Lagrangian sliding fluid element algorithm
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: altLabel "blood-tissue exchange method" xsd:string {comment="EXACT"}
-property_value: altLabel "BTEX" xsd:string {comment="EXACT"}
-property_value: altLabel "LSFEA" xsd:string {comment="EXACT"}
-property_value: definition "Because the analytic solutions to the partial differential equations require convolution integration, solutions are obtained relatively efficiently by a fast numerical method. Our approach centers on the use of a sliding fluid element algorithm for capillary convection, with the time step set equal to the length step divided by the fluid velocity. Radial fluxes by permeation between plasma, interstitial fluid, and cells and axial diffusion exchanges within each time step are calculated analytically. The method enforces mass conservation unless there is regional consumption." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000102 ! spatial description
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000372 ! partial differential equation problem
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
 property_value: seeAlso "http://identifiers.org/pubmed/1449234" xsd:anyURI {comment="Bassingthwaighte JB, Chan IS, and Wang CY. Computationally efficient algorithms for capillary convection-permeation-diffusion models for blood-tissue exchange. Ann Biomed Eng 20: 687-725, 1992."}
+property_value: skos:altLabel "blood-tissue exchange method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "BTEX" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "LSFEA" xsd:string {comment="EXACT"}
+property_value: skos:definition "Because the analytic solutions to the partial differential equations require convolution integration, solutions are obtained relatively efficiently by a fast numerical method. Our approach centers on the use of a sliding fluid element algorithm for capillary convection, with the time step set equal to the length step divided by the fluid velocity. Radial fluxes by permeation between plasma, interstitial fluid, and cells and axial diffusion exchanges within each time step are calculated analytically. The method enforces mass conservation unless there is regional consumption." xsd:string
 
 [Term]
-id: KISAO_0000307
+id: kisao:KISAO_0000307
 name: finite difference method
-is_a: KISAO_0000369 ! partial differential equation discretization method
-property_value: altLabel "FDM" xsd:string {comment="EXACT"}
-property_value: definition "The finite difference method is based on local approximations of the partial derivatives in a Partial Differential Equation, which are derived by low order Taylor series expansions." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000369 ! partial differential equation discretization method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000346 ! mesh-based geometry handling
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/0898715342" xsd:anyURI {comment="Y. Saad. 2003. Iterative Methods for Sparse Linear Systems (2nd ed.). Soc. for Industrial and Applied Math., Philadelphia, PA, USA."}
+property_value: skos:altLabel "FDM" xsd:string {comment="EXACT"}
+property_value: skos:definition "The finite difference method is based on local approximations of the partial derivatives in a Partial Differential Equation, which are derived by low order Taylor series expansions." xsd:string
 
 [Term]
-id: KISAO_0000308
+id: kisao:KISAO_0000308
 name: MacCormack method
-is_a: KISAO_0000307 ! finite difference method
-disjoint_from: KISAO_0000309 ! Crank-Nicolson method
-property_value: definition "In computational fluid dynamics, the MacCormack method is a widely used discretization scheme for the numerical solution of hyperbolic partial differential equations. This second-order finite difference method [http://identifiers.org/biomodels.kisao/KISAO_0000307] is introduced by R. W. MacCormack in 1969." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+is_a: kisao:KISAO_0000307 ! finite difference method
+disjoint_from: kisao:KISAO_0000309 ! Crank-Nicolson method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
 property_value: seeAlso "http://identifiers.org/doi/10.2514/2.6901" xsd:anyURI {comment="MacCormack, R. W., The Effect of viscosity in hypervelocity impact cratering, AIAA Paper, 69-354 (1969)."}
+property_value: skos:definition "In computational fluid dynamics, the MacCormack method is a widely used discretization scheme for the numerical solution of hyperbolic partial differential equations. This second-order finite difference method [http://identifiers.org/biomodels.kisao/KISAO_0000307] is introduced by R. W. MacCormack in 1969." xsd:string
 
 [Term]
-id: KISAO_0000309
+id: kisao:KISAO_0000309
 name: Crank-Nicolson method
-is_a: KISAO_0000307 ! finite difference method
-property_value: definition "In numerical analysis, the Crank-Nicolson method is a finite difference method [http://identifiers.org/biomodels.kisao/KISAO_0000307] used for numerically solving the heat equation and similar partial differential equations. It is a second-order method in time, implicit in time, and is numerically stable. The method was developed by John Crank and Phyllis Nicolson in the mid 20th century." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000307 ! finite difference method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1007/BF02127704" xsd:anyURI {comment="Crank, J.; Nicolson, P. (1947). A practical method for numerical evaluation of solutions of partial differential equations of the heat conduction type. Proc. Camb. Phil. Soc. 43 (1): 50-67."}
+property_value: skos:definition "In numerical analysis, the Crank-Nicolson method is a finite difference method [http://identifiers.org/biomodels.kisao/KISAO_0000307] used for numerically solving the heat equation and similar partial differential equations. It is a second-order method in time, implicit in time, and is numerically stable. The method was developed by John Crank and Phyllis Nicolson in the mid 20th century." xsd:string
 
 [Term]
-id: KISAO_0000310
+id: kisao:KISAO_0000310
 name: method of lines {comment="EXACT"}
-is_a: KISAO_0000369 ! partial differential equation discretization method
-property_value: altLabel "MOL" xsd:string {comment="EXACT"}
-property_value: altLabel "NMOL" xsd:string {comment="EXACT"}
-property_value: altLabel "NUMOL" xsd:string {comment="EXACT"}
-property_value: definition "The method of lines is a general technique for solving partial differential equations (PDEs) by typically using finite difference relationships for the spatial derivatives and ordinary differential equations for the time derivative." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000369 ! partial differential equation discretization method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000107 ! progression with adaptive time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000346 ! mesh-based geometry handling
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/0126241309" xsd:anyURI {comment="Schiesser, W. E. (1991). The Numerical Method of Lines. Academic Press."}
+property_value: skos:altLabel "MOL" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "NMOL" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "NUMOL" xsd:string {comment="EXACT"}
+property_value: skos:definition "The method of lines is a general technique for solving partial differential equations (PDEs) by typically using finite difference relationships for the spatial derivatives and ordinary differential equations for the time derivative." xsd:string
 
 [Term]
-id: KISAO_0000314
+id: kisao:KISAO_0000311
+name: type of domain geometry handling
+is_a: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+
+[Term]
+id: kisao:KISAO_0000314
 name: S-System power-law canonical differential equations solver
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: altLabel "ESSYNS GMA" xsd:string {comment="EXACT"}
-property_value: definition "Ordinary differential equations can be recast into a nonlinear canonical form called an S-system. Evidence for the generality of this class comes from extensive empirical examples that have been recast and from the discovery that sets of differential equations and functions, recognized as among the most general, are special cases of S-systems. Identification of this nonlinear canonical form suggests a radically different approach to numerical solution of ordinary differential equations. By capitalizing on the regular structure of S-systems, efficient formulas for a variable-order, variable-step Taylor-series method are developed. " xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000107 ! progression with adaptive time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0727042" xsd:anyURI {comment="Irvine, D.H. and Savageau, M.A., Efficient solution of nonlinear ordinary differential equations expressed in S-System canonical form, Siam. J. Numer. Anal., 27:704-735, 1990."}
+property_value: skos:altLabel "ESSYNS GMA" xsd:string {comment="EXACT"}
+property_value: skos:definition "Ordinary differential equations can be recast into a nonlinear canonical form called an S-system. Evidence for the generality of this class comes from extensive empirical examples that have been recast and from the discovery that sets of differential equations and functions, recognized as among the most general, are special cases of S-systems. Identification of this nonlinear canonical form suggests a radically different approach to numerical solution of ordinary differential equations. By capitalizing on the regular structure of S-systems, efficient formulas for a variable-order, variable-step Taylor-series method are developed. " xsd:string
 
 [Term]
-id: KISAO_0000315
+id: kisao:KISAO_0000315
 name: lattice gas automata
-is_a: KISAO_0000068 ! deterministic cellular automata update algorithm
-disjoint_from: KISAO_0000334 ! multiparticle lattice gas automata
-property_value: altLabel "lattice gas cellular automata" xsd:string {comment="EXACT"}
-property_value: altLabel "LGA" xsd:string {comment="EXACT"}
-property_value: altLabel "LGCA" xsd:string {comment="EXACT"}
-property_value: definition "Lattice gas automata methods are a series of cellular automata methods used to simulate fluid flows. From the LGCA, it is possible to derive the macroscopic Navier-Stokes equations." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000068 ! deterministic cellular automata update algorithm
+disjoint_from: kisao:KISAO_0000334 ! multiparticle lattice gas automata
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/3-540-66973-6" xsd:anyURI {comment="Dieter A. Wolf-Gladrow (2000). Lattice-Gas Cellular Automata and Lattice Boltzmann Models. Springer."}
+property_value: skos:altLabel "lattice gas cellular automata" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "LGA" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "LGCA" xsd:string {comment="EXACT"}
+property_value: skos:definition "Lattice gas automata methods are a series of cellular automata methods used to simulate fluid flows. From the LGCA, it is possible to derive the macroscopic Navier-Stokes equations." xsd:string
 
 [Term]
-id: KISAO_0000316
+id: kisao:KISAO_0000316
 name: enhanced Greens function reaction dynamics
-is_a: KISAO_0000056 ! Smoluchowski equation based method
-relationship: KISAO_0000359 KISAO_0000058 ! Greens function reaction dynamics
-property_value: altLabel "eGFRD" xsd:string {comment="EXACT"}
-property_value: altLabel "enhanced Greens function reaction dynamics" xsd:string {comment="EXACT"}
-property_value: definition "GFRD [http://identifiers.org/biomodels.kisao/KISAO_0000058] decomposes the multi­body reaction diffusion problem to a set of single and two body problems. Analytical solutions for two body reaction diffusion are available via Smoluchowski equation. eGFRD allows to solve each sub­problem asynchronously by introducing the concept of first passage processes." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000056 ! Smoluchowski equation based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000102 ! spatial description
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000105 ! discrete variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000107 ! progression with adaptive time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000058 ! Greens function reaction dynamics
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1007/978-3-540-88562-7_3" xsd:anyURI {comment="K. Takahashi, An exact Brownian dynamics method for cell simulation, in Computational Methods in Systems Biology, vol. 5307/2008."}
+property_value: skos:altLabel "eGFRD" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "enhanced Greens function reaction dynamics" xsd:string {comment="EXACT"}
+property_value: skos:definition "GFRD [http://identifiers.org/biomodels.kisao/KISAO_0000058] decomposes the multi­body reaction diffusion problem to a set of single and two body problems. Analytical solutions for two body reaction diffusion are available via Smoluchowski equation. eGFRD allows to solve each sub­problem asynchronously by introducing the concept of first passage processes." xsd:string
 
 [Term]
-id: KISAO_0000317
+id: kisao:KISAO_0000317
 name: E-Cell multi-algorithm simulation method
-is_a: KISAO_0000352 ! hybrid method
-property_value: definition "A modular meta-algorithm with a discrete event scheduler that can incorporate any type of time-driven simulation algorithm. It was shown that this meta-algorithm can efficiently drive simulation models with different simulation algorithms with little intrusive modification to the algorithms themselves. Only a few additional methods to handle communications between computational modules are required." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
+is_a: kisao:KISAO_0000352 ! hybrid method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
 property_value: seeAlso "http://identifiers.org/pubmed/14990450" xsd:anyURI {comment="Takahashi, K., Kaizu, K., Hu, B., and Tomita, M., A multi-algorithm, multi-timescale method for cell simulation. Bioinformatics, in press."}
+property_value: skos:definition "A modular meta-algorithm with a discrete event scheduler that can incorporate any type of time-driven simulation algorithm. It was shown that this meta-algorithm can efficiently drive simulation models with different simulation algorithms with little intrusive modification to the algorithms themselves. Only a few additional methods to handle communications between computational modules are required." xsd:string
 
 [Term]
-id: KISAO_0000318
+id: kisao:KISAO_0000318
 name: Gauss-Legendre Runge-Kutta method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: altLabel "Open Formula" xsd:string {comment="EXACT"}
-property_value: definition "So called 'Open Formula', two points formula, three points formula, four points formula, five points formula and six points formula of the Runge-Kutta method to solve the initial value problem of the ordinary differential equation. These formulas use the points and weights from the Gauss-Legendre Quadrature formulas for finding the value of the definite integral." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
 property_value: seeAlso "http://identifiers.org/isbn/960-8457-54-8" xsd:anyURI {comment="Maitree Podisuk, Sirirat Khuntidilokwongsa, and Witchaya Rattanametawee. 2006. Gauss-Legendre Quadrature formula in Runge-Kutta method with modified model of Newton cooling law. In Proceedings of the 8th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering (MMACTEE'06). World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wisconsin, USA, 312-317."}
+property_value: skos:altLabel "Open Formula" xsd:string {comment="EXACT"}
+property_value: skos:definition "So called 'Open Formula', two points formula, three points formula, four points formula, five points formula and six points formula of the Runge-Kutta method to solve the initial value problem of the ordinary differential equation. These formulas use the points and weights from the Gauss-Legendre Quadrature formulas for finding the value of the definite integral." xsd:string
 
 [Term]
-id: KISAO_0000319
+id: kisao:KISAO_0000319
 name: Monte Carlo method
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: altLabel "MC" xsd:string {comment="EXACT"}
-property_value: definition "Monte Carlo methods (or Monte Carlo experiments) are a class of computational algorithms that rely on repeated random sampling to compute their results." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000104 ! stochastic system behaviour
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://identifiers.org/doi/10.2307/2280232" xsd:anyURI {comment="Metropolis, N.; Ulam, S. (1949). \"The Monte Carlo Method\". Journal of the American Statistical Association (American Statistical Association) 44 (247): 335-341."}
+property_value: skos:altLabel "MC" xsd:string {comment="EXACT"}
+property_value: skos:definition "Monte Carlo methods (or Monte Carlo experiments) are a class of computational algorithms that rely on repeated random sampling to compute their results." xsd:string
 
 [Term]
-id: KISAO_0000320
+id: kisao:KISAO_0000320
 name: BioRica hybrid method
-is_a: KISAO_0000352 ! hybrid method
-property_value: definition "The simulation schema for a given BioRica node is given by a hybrid algorithm that deals with continuous time and allows for discrete events that roll back the time according to these discrete interruptions." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "BioRica" xsd:string
+is_a: kisao:KISAO_0000352 ! hybrid method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000107 ! progression with adaptive time step
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "BioRica" xsd:string
 property_value: seeAlso "http://identifiers.org/pubmed/19425152" xsd:anyURI {comment="Cvijovic M, Soueidan H, Sherman DJ, Klipp E, Nikolski M. Exploratory simulation of cell ageing using hierarchical models. Genome Inform. 2008;21:114-25."}
+property_value: skos:definition "The simulation schema for a given BioRica node is given by a hybrid algorithm that deals with continuous time and allows for discrete events that roll back the time according to these discrete interruptions." xsd:string
 
 [Term]
-id: KISAO_0000321
+id: kisao:KISAO_0000321
 name: Cash-Karp method
-is_a: KISAO_0000435 ! embedded Runge-Kutta 5(4) method
-property_value: definition "An family of explicit Runge-Kutta formulas, which are very efficient for problems with smooth solution as well as problems having rapidly varying solutions. Each member of this family consists of a fifty-order formula that contains embedded formulas of all orders 1 through 4. By computing solutions at several different orders, it is possible to detect sharp fronts or discontinuities before all the function evaluations defining the full Runge-Kutta step have been computed." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "Cain" xsd:string
-property_value: isImplementedIn "GSL" xsd:string
+is_a: kisao:KISAO_0000435 ! embedded Runge-Kutta 5(4) method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "Cain" xsd:string
+property_value: kisao:isImplementedIn "GSL" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1145/79505.79507" xsd:anyURI {comment="J. R. Cash, A. H. Karp. \"A variable order Runge-Kutta method for initial value problems with rapidly varying right-hand sides\", ACM Transactions on Mathematical Software 16: 201-222, 1990."}
+property_value: skos:definition "An family of explicit Runge-Kutta formulas, which are very efficient for problems with smooth solution as well as problems having rapidly varying solutions. Each member of this family consists of a fifty-order formula that contains embedded formulas of all orders 1 through 4. By computing solutions at several different orders, it is possible to detect sharp fronts or discontinuities before all the function evaluations defining the full Runge-Kutta step have been computed." xsd:string
 
 [Term]
-id: KISAO_0000323
+id: kisao:KISAO_0000322
+name: hybridity
+is_a: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "The basic idea of hybrid simulation methods is to combine the advantages of complementary simulation approaches: the whole system is subdivided into appropriate parts and different simulation methods operate on these parts at the same time." xsd:string
+
+[Term]
+id: kisao:KISAO_0000323
 name: equation-free probabilistic steady-state approximation
-is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
-property_value: definition "We present a probabilistic steady-state approximation that separates the time scales of an arbitrary reaction network, detects the convergence of a marginal distribution to a quasi-steady-state, directly samples the underlying distribution, and uses those samples to accurately predict the state of the system, including the effects of the slow dynamics, at future times. The numerical method produces an accurate solution of both the fast and slow reaction dynamics while, for stiff systems, reducing the computational time by orders of magnitude. The developed theory makes no approximations on the shape or form of the underlying steady-state distribution and only assumes that it is ergodic. <...> The developed theory may be applied to any type of kinetic Monte Carlo simulation to more efficiently simulate dynamically stiff systems, including existing exact, approximate, or hybrid stochastic simulation techniques.\n" xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000333 ! accelerated stochastic simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000325 ! minimum fast/discrete reaction occurrences number
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000326 ! number of samples
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000327 ! maximum discrete number
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000328 ! minimum fast rate
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2131050" xsd:anyURI {comment="Salis H, Kaznessis YN. An equation-free probabilistic steady-state approximation: dynamic application to the stochastic simulation of biochemical reaction networks. J Chem Phys. 2005 Dec 1;123(21):214106."}
+property_value: skos:definition "We present a probabilistic steady-state approximation that separates the time scales of an arbitrary reaction network, detects the convergence of a marginal distribution to a quasi-steady-state, directly samples the underlying distribution, and uses those samples to accurately predict the state of the system, including the effects of the slow dynamics, at future times. The numerical method produces an accurate solution of both the fast and slow reaction dynamics while, for stiff systems, reducing the computational time by orders of magnitude. The developed theory makes no approximations on the shape or form of the underlying steady-state distribution and only assumes that it is ergodic. <...> The developed theory may be applied to any type of kinetic Monte Carlo simulation to more efficiently simulate dynamically stiff systems, including existing exact, approximate, or hybrid stochastic simulation techniques.\n" xsd:string
 
 [Term]
-id: KISAO_0000324
+id: kisao:KISAO_0000324
 name: nested stochastic simulation algorithm
-is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
-relationship: KISAO_0000360 KISAO_0000029 ! Gillespie direct algorithm
-property_value: altLabel "nested SSA" xsd:string {comment="EXACT"}
-property_value: definition "This multiscale method is a small modification of the Gillespie's direct method [http://identifiers.org/biomodels.kisao/KISAO_0000029], in the form of a nested SSA, with inner loops for the fast reactions, and outer loop for the slow reactions. The number of groups can be more than two, and the grouping into fast and slow  variables can be done dynamically in an adaptive version of the scheme." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000333 ! accelerated stochastic simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000029 ! Gillespie direct algorithm
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/pubmed/16321076" xsd:anyURI {comment="E W., Liu D. and Vanden-Eijnden E. Nested stochastic simulation algorithm for chemical kinetic systems with disparate rates. J Chem Phys. 2005 Nov 15;123(19):194107.\n"}
+property_value: skos:altLabel "nested SSA" xsd:string {comment="EXACT"}
+property_value: skos:definition "This multiscale method is a small modification of the Gillespie's direct method [http://identifiers.org/biomodels.kisao/KISAO_0000029], in the form of a nested SSA, with inner loops for the fast reactions, and outer loop for the slow reactions. The number of groups can be more than two, and the grouping into fast and slow  variables can be done dynamically in an adaptive version of the scheme." xsd:string
+
+[Term]
+id: kisao:KISAO_0000325
+name: minimum fast/discrete reaction occurrences number
+is_a: kisao:KISAO_0000242 ! error control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000323 {all_only="true"} ! equation-free probabilistic steady-state approximation
+property_value: dc:creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2131050" xsd:anyURI {comment="Salis H, Kaznessis YN. An equation-free probabilistic steady-state approximation: dynamic application to the stochastic simulation of biochemical reaction networks. J Chem Phys. 2005 Dec 1;123(21):214106."}
+property_value: skos:definition "Parameter of 'equation-free probabilistic steady-state approximation' method  [http://identifiers.org/biomodels.kisao/KISAO_0000323], which describes the minimum number of fast/discrete reaction occurrences before their effects cause convergence to a quasi-steady-state distribution." xsd:string
+
+[Term]
+id: kisao:KISAO_0000326
+name: number of samples
+is_a: kisao:KISAO_0000242 ! error control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000323 {all_only="true"} ! equation-free probabilistic steady-state approximation
+property_value: dc:creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2131050" xsd:anyURI {comment="Salis H, Kaznessis YN. An equation-free probabilistic steady-state approximation: dynamic application to the stochastic simulation of biochemical reaction networks. J Chem Phys. 2005 Dec 1;123(21):214106."}
+property_value: skos:definition "Parameter of 'equation-free probabilistic steady-state approximation' method [http://identifiers.org/biomodels.kisao/KISAO_0000323], which determines the number of samples taken from the distribution." xsd:string
+
+[Term]
+id: kisao:KISAO_0000327
+name: maximum discrete number
+is_a: kisao:KISAO_0000252 ! partitioning control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000323 {all_only="true"} ! equation-free probabilistic steady-state approximation
+property_value: dc:creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2131050" xsd:anyURI {comment="Salis H, Kaznessis YN. An equation-free probabilistic steady-state approximation: dynamic application to the stochastic simulation of biochemical reaction networks. J Chem Phys. 2005 Dec 1;123(21):214106."}
+property_value: skos:definition "Parameter of 'equation-free probabilistic steady-state approximation' method [http://identifiers.org/biomodels.kisao/KISAO_0000323], which controls the maximum number of molecules of some reactant species in order for the reaction to be considered discrete." xsd:string
 
 [Term]
-id: KISAO_0000329
+id: kisao:KISAO_0000328
+name: minimum fast rate
+is_a: kisao:KISAO_0000252 ! partitioning control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000323 {all_only="true"} ! equation-free probabilistic steady-state approximation
+property_value: dc:creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2131050" xsd:anyURI {comment="Salis H, Kaznessis YN. An equation-free probabilistic steady-state approximation: dynamic application to the stochastic simulation of biochemical reaction networks. J Chem Phys. 2005 Dec 1;123(21):214106."}
+property_value: skos:definition "Parameter of 'equation-free probabilistic steady-state approximation' method [http://identifiers.org/biomodels.kisao/KISAO_0000323], which controls the minimum rate of the reaction in order for it to be considered fast." xsd:string
+
+[Term]
+id: kisao:KISAO_0000329
 name: constant-time kinetic Monte Carlo algorithm
-is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
-property_value: altLabel "SSA-CR" xsd:string {comment="EXACT"}
-property_value: definition "The computational cost of the original SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] scaled linearly with the number of reactions in the network. Gibson and Bruck developed a logarithmic scaling version of the SSA which uses a priority queue or binary tree for more efficient reaction selection [http://identifiers.org/biomodels.kisao/KISAO_0000027]. More generally, this problem is one of dynamic discrete random variate generation which finds many uses in kinetic Monte Carlo and discrete event simulation. We present here a constant-time algorithm, whose cost is independent of the number of reactions, enabled by a slightly more complex underlying data structure." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000333 ! accelerated stochastic simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/pubmed/18513044" xsd:anyURI {comment="Slepoy A, Thompson AP, Plimpton SJ. A constant-time kinetic Monte Carlo algorithm for simulation of large biochemical reaction networks. J Chem Phys. 2008 May 28;128(20):205101."}
+property_value: skos:altLabel "SSA-CR" xsd:string {comment="EXACT"}
+property_value: skos:definition "The computational cost of the original SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] scaled linearly with the number of reactions in the network. Gibson and Bruck developed a logarithmic scaling version of the SSA which uses a priority queue or binary tree for more efficient reaction selection [http://identifiers.org/biomodels.kisao/KISAO_0000027]. More generally, this problem is one of dynamic discrete random variate generation which finds many uses in kinetic Monte Carlo and discrete event simulation. We present here a constant-time algorithm, whose cost is independent of the number of reactions, enabled by a slightly more complex underlying data structure." xsd:string
 
 [Term]
-id: KISAO_0000330
+id: kisao:KISAO_0000330
 name: R-leaping algorithm
-is_a: KISAO_0000621 ! stochastic simulation leaping method
-property_value: altLabel "R-leap method" xsd:string {comment="EXACT"}
-property_value: definition "A novel algorithm is proposed for the acceleration of the exact stochastic simulation algorithm by a predefined number of reaction firings (R-leaping) that may occur across several reaction channels. In the present approach, the numbers of reaction firings are correlated binomial distributions and the sampling procedure is independent of any permutation of the reaction channels. This enables the algorithm to efficiently handle large systems with disparate rates, providing substantial computational savings in certain cases." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000621 ! stochastic simulation leaping method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/pubmed/16964997" xsd:anyURI {comment="Auger A, Chatelain P, Koumoutsakos P. R-leaping: accelerating the stochastic simulation algorithm by reaction leaps. J Chem Phys. 2006 Aug 28;125(8):084103."}
+property_value: skos:altLabel "R-leap method" xsd:string {comment="EXACT"}
+property_value: skos:definition "A novel algorithm is proposed for the acceleration of the exact stochastic simulation algorithm by a predefined number of reaction firings (R-leaping) that may occur across several reaction channels. In the present approach, the numbers of reaction firings are correlated binomial distributions and the sampling procedure is independent of any permutation of the reaction channels. This enables the algorithm to efficiently handle large systems with disparate rates, providing substantial computational savings in certain cases." xsd:string
 
 [Term]
-id: KISAO_0000331
+id: kisao:KISAO_0000331
 name: exact R-leaping algorithm
-is_a: KISAO_0000621 ! stochastic simulation leaping method
-relationship: KISAO_0000359 KISAO_0000330 ! R-leaping algorithm
-property_value: altLabel "ER-leap method" xsd:string {comment="EXACT"}
-property_value: altLabel "exact accelerated stochastic simulation algorithm" xsd:string {comment="EXACT"}
-property_value: altLabel "exact R-leap method" xsd:string {comment="EXACT"}
-property_value: definition "We present a SSA which, similar to R-leap [http://identifiers.org/biomodels.kisao/KISAO_0000330], accelerates SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] by executing multiple reactions per algorithmic step, but which samples the reactant trajectories from the same probability distribution as the SSA. This 'exact R-leap' or 'ER-leap' algorithm is a modification of the R-leap algorithm which is both exact and capable of substantial speed-up over SSA." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000621 ! stochastic simulation leaping method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000330 ! R-leaping algorithm
+property_value: dc:creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/2852436" xsd:anyURI {comment="Eric Mjolsness, David Orendorff, Philippe Chatelain, and Petros Koumoutsakos. An exact accelerated stochastic simulation algorithm. J Chem Phys. 2009 April 14; 130(14): 144110."}
+property_value: skos:altLabel "ER-leap method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "exact accelerated stochastic simulation algorithm" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "exact R-leap method" xsd:string {comment="EXACT"}
+property_value: skos:definition "We present a SSA which, similar to R-leap [http://identifiers.org/biomodels.kisao/KISAO_0000330], accelerates SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] by executing multiple reactions per algorithmic step, but which samples the reactant trajectories from the same probability distribution as the SSA. This 'exact R-leap' or 'ER-leap' algorithm is a modification of the R-leap algorithm which is both exact and capable of substantial speed-up over SSA." xsd:string
+
+[Term]
+id: kisao:KISAO_0000332
+name: ER-leap initial leap
+is_a: kisao:KISAO_0000244 ! granularity control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000331 {all_only="true"} ! exact R-leaping algorithm
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/pubmed/2852436" xsd:anyURI {comment="Eric Mjolsness, David Orendorff, Philippe Chatelain, and Petros Koumoutsakos. An exact accelerated stochastic simulation algorithm. J Chem Phys. 2009 April 14; 130(14): 144110."}
+property_value: skos:altLabel "L" xsd:string {comment="EXACT"}
+property_value: skos:definition "L (initial step) is a parameter of 'exact R-leaping method' [http://identifiers.org/biomodels.kisao/KISAO_0000331]. ''We will assume that the reaction event to be bounded occurs within a run of L events in the SSA algorithm[http://identifiers.org/biomodels.kisao/KISAO_0000029], in order to execute L reactions at once in the manner of the R-leap algorithm[http://identifiers.org/biomodels.kisao/KISAO_0000230]''." xsd:string
 
 [Term]
-id: KISAO_0000333
+id: kisao:KISAO_0000333
 name: accelerated stochastic simulation algorithm
-is_a: KISAO_0000241 ! Gillespie-like method
-relationship: KISAO_0000359 KISAO_0000029 ! Gillespie direct algorithm
-property_value: altLabel "accelerated SSA" xsd:string {comment="EXACT"}
-property_value: definition "An algorithm, which accelerates SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] either at the expense of its accuracy or exact." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000241 ! Gillespie-like method
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000029 ! Gillespie direct algorithm
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:altLabel "accelerated SSA" xsd:string {comment="EXACT"}
+property_value: skos:definition "An algorithm, which accelerates SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] either at the expense of its accuracy or exact." xsd:string
 
 [Term]
-id: KISAO_0000334
+id: kisao:KISAO_0000334
 name: multiparticle lattice gas automata
-is_a: KISAO_0000068 ! deterministic cellular automata update algorithm
-relationship: KISAO_0000359 KISAO_0000315 ! lattice gas automata
-property_value: altLabel "multiparticle lattice gas cellular automata" xsd:string {comment="EXACT"}
-property_value: definition "An algorithm which allows  for an arbitrary number of particles, while keeping the benefits of the cellular automata approach [http://identifiers.org/biomodels.kisao/KISAO_0000315]." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000068 ! deterministic cellular automata update algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000315 ! lattice gas automata
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1142/S0129183194000052" xsd:anyURI {comment="Chopard B., et al.Multiparticle lattice gas automata for reaction diffusion systems. Int. J. Mod. Phys. C 1994;5:47-63."}
+property_value: skos:altLabel "multiparticle lattice gas cellular automata" xsd:string {comment="EXACT"}
+property_value: skos:definition "An algorithm which allows  for an arbitrary number of particles, while keeping the benefits of the cellular automata approach [http://identifiers.org/biomodels.kisao/KISAO_0000315]." xsd:string
 
 [Term]
-id: KISAO_0000335
+id: kisao:KISAO_0000335
 name: generalized stochastic simulation algorithm
-is_a: KISAO_0000241 ! Gillespie-like method
-relationship: KISAO_0000361 KISAO_0000029 ! Gillespie direct algorithm
-property_value: definition "Gillespie direct method [http://identifiers.org/biomodels.kisao/KISAO_0000029] follows unit-by-unit changes in the total numbers of each reactant species, it is especially well suited to the study of systems in which reactant densities are low and the application of methods based on continuum approximations, such as the traditional ordinary differential equations of chemical kinetics, is questionable. The 'generalized stochastic simulation algorithm' branch presents methods, which extend Gillespie direct method [http://identifiers.org/biomodels.kisao/KISAO_0000029] to suit to systems with other characteristics." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000241 ! Gillespie-like method
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000029 ! Gillespie direct algorithm
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Gillespie direct method [http://identifiers.org/biomodels.kisao/KISAO_0000029] follows unit-by-unit changes in the total numbers of each reactant species, it is especially well suited to the study of systems in which reactant densities are low and the application of methods based on continuum approximations, such as the traditional ordinary differential equations of chemical kinetics, is questionable. The 'generalized stochastic simulation algorithm' branch presents methods, which extend Gillespie direct method [http://identifiers.org/biomodels.kisao/KISAO_0000029] to suit to systems with other characteristics." xsd:string
 
 [Term]
-id: KISAO_0000336
+id: kisao:KISAO_0000336
 name: D-leaping method
-is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
-property_value: definition "We propose a novel, accelerated algorithm for the approximate stochastic simulation of biochemical systems with delays. The present work extends existing accelerated algorithms by distributing, in a time adaptive fashion, the delayed reactions so as to minimize the computational effort while preserving their accuracy." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000335 ! generalized stochastic simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1016/j.jcp.2009.05.004" xsd:anyURI {comment="Bayati B, Chatelain P, Koumoutsakos. D-leaping: Accelerating stochastic simulation algorithms for reactions with delays. Journal of Computational Physics. 2009 Sept;228(16):5909-5918."}
+property_value: skos:definition "We propose a novel, accelerated algorithm for the approximate stochastic simulation of biochemical systems with delays. The present work extends existing accelerated algorithms by distributing, in a time adaptive fashion, the delayed reactions so as to minimize the computational effort while preserving their accuracy." xsd:string
 
 [Term]
-id: KISAO_0000337
+id: kisao:KISAO_0000337
 name: finite element method
-is_a: KISAO_0000369 ! partial differential equation discretization method
-property_value: altLabel "FEA" xsd:string {comment="EXACT"}
-property_value: altLabel "FEM" xsd:string {comment="EXACT"}
-property_value: altLabel "finite element analysis" xsd:string {comment="EXACT"}
-property_value: definition "A numerical technique for finding approximate solutions of partial differential equations (PDE) as well as of integral equations. The solution approach is based either on eliminating the differential equation completely (steady state problems), or rendering the PDE into an approximating system of ordinary differential equations, which are then numerically integrated using standard techniques such as Euler method [http://identifiers.org/biomodels.kisao/KISAO_0000261], Runge-Kutta [http://identifiers.org/biomodels.kisao/KISAO_0000064], etc." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000369 ! partial differential equation discretization method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000346 ! mesh-based geometry handling
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1109/MAP.2007.376627" xsd:anyURI {comment="Pelosi G. The finite-element method, Part I: R. L. Courant: Historical Corner. IEEE Antennas and Propagation Magazine, Vol. 49, No. 2. (April 2007), pp. 180-182."}
+property_value: skos:altLabel "FEA" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "FEM" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "finite element analysis" xsd:string {comment="EXACT"}
+property_value: skos:definition "A numerical technique for finding approximate solutions of partial differential equations (PDE) as well as of integral equations. The solution approach is based either on eliminating the differential equation completely (steady state problems), or rendering the PDE into an approximating system of ordinary differential equations, which are then numerically integrated using standard techniques such as Euler method [http://identifiers.org/biomodels.kisao/KISAO_0000261], Runge-Kutta [http://identifiers.org/biomodels.kisao/KISAO_0000064], etc." xsd:string
 
 [Term]
-id: KISAO_0000338
+id: kisao:KISAO_0000338
 name: h-version of the finite element method
-is_a: KISAO_0000337 ! finite element method
-disjoint_from: KISAO_0000339 ! p-version of the finite element method
-property_value: altLabel "h-FEM" xsd:string {comment="EXACT"}
-property_value: altLabel "h-method" xsd:string {comment="EXACT"}
-property_value: definition "Classical form of the 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337], in which polynomials of fixed degree p are used and the mesh is refined to increase accuracy. Can be considered as a special case of the h-p version [http://identifiers.org/biomodels.kisao/KISAO_0000340]." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000337 ! finite element method
+disjoint_from: kisao:KISAO_0000339 ! p-version of the finite element method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1016/0168-874X(94)90003-5" xsd:anyURI {comment="Babuska, I., T. Strouboulis, A. Mathur, C. S. Upadhyay, Pollution error in the h-version of the finite element method and the local quality of a-posteriori error estimators, Finite Elements in Analysis and Design, 17: 273-321, 1994."}
+property_value: skos:altLabel "h-FEM" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "h-method" xsd:string {comment="EXACT"}
+property_value: skos:definition "Classical form of the 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337], in which polynomials of fixed degree p are used and the mesh is refined to increase accuracy. Can be considered as a special case of the h-p version [http://identifiers.org/biomodels.kisao/KISAO_0000340]." xsd:string
 
 [Term]
-id: KISAO_0000339
+id: kisao:KISAO_0000339
 name: p-version of the finite element method
-is_a: KISAO_0000337 ! finite element method
-property_value: altLabel "p-FEM" xsd:string {comment="EXACT"}
-property_value: altLabel "p-method" xsd:string {comment="EXACT"}
-property_value: definition "The p version of 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] uses a fixed mesh but increases the polynomial degree p to increase accuracy. Can be considered as a special case of the h-p version [http://identifiers.org/biomodels.kisao/KISAO_0000340]." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000337 ! finite element method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0718033" xsd:anyURI {comment="Babuska, I., B.A. Szabo and I.N. Katz, The p-version of the finite element method, SIAM J. Numer. Anal., 18: 515-545, 1981."}
+property_value: skos:altLabel "p-FEM" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "p-method" xsd:string {comment="EXACT"}
+property_value: skos:definition "The p version of 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] uses a fixed mesh but increases the polynomial degree p to increase accuracy. Can be considered as a special case of the h-p version [http://identifiers.org/biomodels.kisao/KISAO_0000340]." xsd:string
 
 [Term]
-id: KISAO_0000340
+id: kisao:KISAO_0000340
 name: h-p version of the finite element method
-is_a: KISAO_0000337 ! finite element method
-disjoint_from: KISAO_0000341 ! mixed finite element method
-relationship: KISAO_0000361 KISAO_0000338 ! h-version of the finite element method
-relationship: KISAO_0000361 KISAO_0000339 ! p-version of the finite element method
-property_value: altLabel "hp-FEM" xsd:string {comment="EXACT"}
-property_value: altLabel "hp-method" xsd:string {comment="EXACT"}
-property_value: definition "In h-p version of 'finite difference method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] the two approaches of mesh refinement and degree enchacement are combined." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000337 ! finite element method
+disjoint_from: kisao:KISAO_0000341 ! mixed finite element method
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000338 ! h-version of the finite element method
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000339 ! p-version of the finite element method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1007/BF00272624" xsd:anyURI {comment="Babuska, I., and B. Guo, The h-p version of the finite element method, Comput. Mech., 1: 203-220, 1986."}
+property_value: skos:altLabel "hp-FEM" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "hp-method" xsd:string {comment="EXACT"}
+property_value: skos:definition "In h-p version of 'finite difference method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] the two approaches of mesh refinement and degree enchacement are combined." xsd:string
 
 [Term]
-id: KISAO_0000341
+id: kisao:KISAO_0000341
 name: mixed finite element method
-is_a: KISAO_0000337 ! finite element method
-property_value: definition "A 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] in which both stress and displacement fields are approximated as primary variables." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000337 ! finite element method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1016/0045-7825(90)90168-L" xsd:anyURI {comment="D. N. Arnold. 1990. Mixed finite element methods for elliptic problems. Comput. Methods Appl. Mech. Eng. 82, 1-3 (September 1990), 281-300."}
+property_value: skos:definition "A 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] in which both stress and displacement fields are approximated as primary variables." xsd:string
 
 [Term]
-id: KISAO_0000342
+id: kisao:KISAO_0000342
 name: level set method
-is_a: KISAO_0000369 ! partial differential equation discretization method
-property_value: altLabel "level-set method" xsd:string {comment="EXACT"}
-property_value: altLabel "LSM" xsd:string {comment="EXACT"}
-property_value: definition "An algorithm for moving surfaces under their curvature. This algorithm rely on numerically solving Hamilton-Jacobi equations with viscous terms, using approximation techniques from hyperbolic conservation laws." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000369 ! partial differential equation discretization method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1016/0021-9991(88)90002-2" xsd:anyURI {comment="Osher, S.; Sethian, J. A. (1988), \"Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations\", J. Comput. Phys. 79: 12-49."}
+property_value: skos:altLabel "level-set method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "LSM" xsd:string {comment="EXACT"}
+property_value: skos:definition "An algorithm for moving surfaces under their curvature. This algorithm rely on numerically solving Hamilton-Jacobi equations with viscous terms, using approximation techniques from hyperbolic conservation laws." xsd:string
 
 [Term]
-id: KISAO_0000343
+id: kisao:KISAO_0000343
 name: generalized finite element method
-is_a: KISAO_0000369 ! partial differential equation discretization method
-relationship: KISAO_0000361 KISAO_0000337 ! finite element method
-property_value: altLabel "GFEM" xsd:string {comment="EXACT"}
-property_value: altLabel "partition of unity method" xsd:string {comment="EXACT"}
-property_value: altLabel "PUM" xsd:string {comment="EXACT"}
-property_value: definition "The GFEM is a generalization of the classical 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] — in its h [http://identifiers.org/biomodels.kisao/KISAO_0000338], p [http://identifiers.org/biomodels.kisao/KISAO_0000339], and h-p versions [http://identifiers.org/biomodels.kisao/KISAO_0000340]— as well as of the various forms of meshless methods used in engineering." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000369 ! partial differential equation discretization method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000347 ! meshless geometry handling
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000337 ! finite element method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1142/S0219876204000083" xsd:anyURI {comment="Babuska, Ivo; Uday Banerjee, John E. Osborn (June 2004). Generalized Finite Element Methods: Main Ideas, Results, and Perspective. International Journal of Computational Methods 1 (1): 67-103."}
+property_value: skos:altLabel "GFEM" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "partition of unity method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "PUM" xsd:string {comment="EXACT"}
+property_value: skos:definition "The GFEM is a generalization of the classical 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] — in its h [http://identifiers.org/biomodels.kisao/KISAO_0000338], p [http://identifiers.org/biomodels.kisao/KISAO_0000339], and h-p versions [http://identifiers.org/biomodels.kisao/KISAO_0000340]— as well as of the various forms of meshless methods used in engineering." xsd:string
 
 [Term]
-id: KISAO_0000345
+id: kisao:KISAO_0000345
 name: h-p cloud method
-is_a: KISAO_0000369 ! partial differential equation discretization method
-property_value: altLabel "h-p clouds" xsd:string {comment="EXACT"}
-property_value: altLabel "method of clouds" xsd:string {comment="EXACT"}
-property_value: definition "A meshless method, which uses a partition of unity to construct the family of h-p cloud functions. " xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000369 ! partial differential equation discretization method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000347 ! meshless geometry handling
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1002/(SICI)1098-2426(199611)12:6<673::AID-NUM3>3.0.CO;2-P" xsd:anyURI {comment="Duarte, C. A. and Oden, J. T. (1996), H-p clouds—an h-p meshless method. Numerical Methods for Partial Differential Equations, 12: 673-705."}
+property_value: skos:altLabel "h-p clouds" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "method of clouds" xsd:string {comment="EXACT"}
+property_value: skos:definition "A meshless method, which uses a partition of unity to construct the family of h-p cloud functions. " xsd:string
 
 [Term]
-id: KISAO_0000348
+id: kisao:KISAO_0000346
+name: mesh-based geometry handling
+is_a: kisao:KISAO_0000311 ! type of domain geometry handling
+disjoint_from: kisao:KISAO_0000347 ! meshless geometry handling
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "In most large-scale numerical simulations of physical phenomena, a large percentage of the overall computational effort is expended on technical details connected with meshing. These details include, in particular, grid generation, mesh adaptation to domain geometry, element or cell connectivity, grid motion and separation to model fracture, fragmentation, free surfaces, etc." xsd:string
+
+[Term]
+id: kisao:KISAO_0000347
+name: meshless geometry handling
+is_a: kisao:KISAO_0000311 ! type of domain geometry handling
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "Most meshless methods require a scattered set of nodal points in the domain of interest. In these methods, there may be no fixed connectivities between the nodes, unlike the finite element or finite difference methods. This feature has significant implications in modeling some physical phenomena that are characterized by a continuous change in the geometry of the domain under analysis. " xsd:string
+
+[Term]
+id: kisao:KISAO_0000348
 name: extended finite element method
-is_a: KISAO_0000369 ! partial differential equation discretization method
-relationship: KISAO_0000361 KISAO_0000337 ! finite element method
-property_value: altLabel "X-FEM" xsd:string {comment="EXACT"}
-property_value: altLabel "XFEM" xsd:string {comment="EXACT"}
-property_value: definition "A numerical method to model arbitrary discontinuities in continuous bodies that does not require the mesh to conform to the discontinuities nor significant mesh refinement near singularities. In X-FEM the standard finite element approximation [http://identifiers.org/biomodels.kisao/KISAO_0000337] is enriched and the approximation space is extended by an additional family of functions." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000369 ! partial differential equation discretization method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000347 ! meshless geometry handling
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000337 ! finite element method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1007/s00466-002-0391-2" xsd:anyURI {comment="Stazi, F. L.; Budyn, E.; Chessa, J.; Belytschko, T. An extended finite element method with higher-order elements for curved cracks. Computational Mechanics, Volume 31, Issue 1-2, pp. 38-48 (2003)."}
+property_value: skos:altLabel "X-FEM" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "XFEM" xsd:string {comment="EXACT"}
+property_value: skos:definition "A numerical method to model arbitrary discontinuities in continuous bodies that does not require the mesh to conform to the discontinuities nor significant mesh refinement near singularities. In X-FEM the standard finite element approximation [http://identifiers.org/biomodels.kisao/KISAO_0000337] is enriched and the approximation space is extended by an additional family of functions." xsd:string
 
 [Term]
-id: KISAO_0000349
+id: kisao:KISAO_0000349
 name: method of finite spheres
-is_a: KISAO_0000369 ! partial differential equation discretization method
-property_value: altLabel "MFS" xsd:string {comment="EXACT"}
-property_value: definition "Method of finite spheres is truly meshless in the sense that the nodes are placed and the numerical integration is performed without a mesh. Some of the novel features of the method of finite spheres are the numerical integration scheme and the way in which the Dirichlet boundary conditions are incorporated." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000369 ! partial differential equation discretization method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000347 ! meshless geometry handling
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1007/s004660050481" xsd:anyURI {comment="S. De and K. J. Bathe. The method of finite spheres. Computational Mechanics, Volume 25, Number 4, 329-345."}
+property_value: skos:altLabel "MFS" xsd:string {comment="EXACT"}
+property_value: skos:definition "Method of finite spheres is truly meshless in the sense that the nodes are placed and the numerical integration is performed without a mesh. Some of the novel features of the method of finite spheres are the numerical integration scheme and the way in which the Dirichlet boundary conditions are incorporated." xsd:string
 
 [Term]
-id: KISAO_0000350
+id: kisao:KISAO_0000350
 name: probability-weighted dynamic Monte Carlo method
-is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
-property_value: altLabel "probability-weighted DMC" xsd:string {comment="EXACT"}
-property_value: altLabel "PW-DMC" xsd:string {comment="EXACT"}
-property_value: definition "We have developed a probability-weighted DMC method by incorporating the weighted sampling algorithm of equilibrium molecular simulations. This new algorithm samples the slow reactions very efficiently and makes it possible to simulate in a computationally efficient manner the reaction kinetics of physical systems in which the rates of reactions vary by several orders of magnitude." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000333 ! accelerated stochastic simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1021/jp011404w" xsd:anyURI {comment="Resat H, Wiley HS, Dixon DA. Probability-weighted dynamic Monte Carlo method for reaction kinetics simulations. J Phys Chem B. 2001;105:11026-11034."}
+property_value: skos:altLabel "probability-weighted DMC" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "PW-DMC" xsd:string {comment="EXACT"}
+property_value: skos:definition "We have developed a probability-weighted DMC method by incorporating the weighted sampling algorithm of equilibrium molecular simulations. This new algorithm samples the slow reactions very efficiently and makes it possible to simulate in a computationally efficient manner the reaction kinetics of physical systems in which the rates of reactions vary by several orders of magnitude." xsd:string
 
 [Term]
-id: KISAO_0000351
+id: kisao:KISAO_0000351
 name: multinomial tau-leaping method
-is_a: KISAO_0000039 ! tau-leaping method
-relationship: KISAO_0000361 KISAO_0000074 ! binomial tau-leaping method
-property_value: altLabel "MtauL" xsd:string {comment="EXACT"}
-property_value: definition "The multinomial tau-leaping method  is an extension of the binomial tau-leaping method [http://identifiers.org/biomodels.kisao/KISAO_0000074] to networks with arbitrary multiple-channel reactant dependencies. Improvements were achieved by a combination of three factors: First, tau-leaping steps are determined simply and efficiently using a-priori information and Poisson distribution based estimates of expectation values for reaction numbers. Second, networks are partitioned into closed groups of reactions and corresponding reactants in which no group reactant set is found in any other group. Third, product formation is factored into upper bound estimation of the number of times a particular reaction occurs." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000039 ! tau-leaping method
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000074 ! binomial tau-leaping method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/pubmed/17343434" xsd:anyURI {comment="Pettigrew MF, Resat H. Multinomial tau-leaping method for stochastic kinetic simulations. J Chem Phys. 2007 Feb 28;126(8):084101."}
+property_value: skos:altLabel "MtauL" xsd:string {comment="EXACT"}
+property_value: skos:definition "The multinomial tau-leaping method  is an extension of the binomial tau-leaping method [http://identifiers.org/biomodels.kisao/KISAO_0000074] to networks with arbitrary multiple-channel reactant dependencies. Improvements were achieved by a combination of three factors: First, tau-leaping steps are determined simply and efficiently using a-priori information and Poisson distribution based estimates of expectation values for reaction numbers. Second, networks are partitioned into closed groups of reactions and corresponding reactants in which no group reactant set is found in any other group. Third, product formation is factored into upper bound estimation of the number of times a particular reaction occurs." xsd:string
 
 [Term]
-id: KISAO_0000352
+id: kisao:KISAO_0000352
 name: hybrid method
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-relationship: KISAO_0000246 KISAO_0000000 ! modelling and simulation algorithm
-property_value: definition "A simulation methods which combines the advantages of complementary simulation approaches: the whole system is subdivided into appropriate parts and different simulation methods operate on these parts at the same time." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000322 ! hybridity
+relationship: kisao:KISAO_0000246 kisao:KISAO_0000000 ! modelling and simulation algorithm
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A simulation methods which combines the advantages of complementary simulation approaches: the whole system is subdivided into appropriate parts and different simulation methods operate on these parts at the same time." xsd:string
 
 [Term]
-id: KISAO_0000353
+id: kisao:KISAO_0000353
 name: generalized minimal residual algorithm
-is_a: KISAO_0000354 ! Krylov subspace projection method
-disjoint_from: KISAO_0000357 ! conjugate gradient method
-relationship: KISAO_0000361 KISAO_0000388 ! minimal residual method
-property_value: altLabel "GMRES" xsd:string {comment="EXACT"}
-property_value: definition "An iterative method for solving linear systems, which has the property of minimizing at every step the norm of the residual vector over a Krylov subspace. The generalized minimal residual method extends the minimal residual method (MINRES) [http://identifiers.org/biomodels.kisao/KISAO_0000388], which is only applicable to symmetric systems, to non-symmetric systems." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "CVODE" xsd:string
+is_a: kisao:KISAO_0000354 ! Krylov subspace projection method
+disjoint_from: kisao:KISAO_0000357 ! conjugate gradient method
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000388 ! minimal residual method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "CVODE" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0907058" xsd:anyURI {comment="Youcef Saad and Martin H. Schultz, GMRES: A Generalized Minimal Residual Algorithm for Solving Nonsymmetric Linear Systems. SIAM J. Sci. and Stat. Comput. 7, 856 (1986)."}
+property_value: skos:altLabel "GMRES" xsd:string {comment="EXACT"}
+property_value: skos:definition "An iterative method for solving linear systems, which has the property of minimizing at every step the norm of the residual vector over a Krylov subspace. The generalized minimal residual method extends the minimal residual method (MINRES) [http://identifiers.org/biomodels.kisao/KISAO_0000388], which is only applicable to symmetric systems, to non-symmetric systems." xsd:string
 
 [Term]
-id: KISAO_0000354
+id: kisao:KISAO_0000354
 name: Krylov subspace projection method
-is_a: KISAO_0000398 ! iterative method for solving a system of linear equations
-property_value: altLabel "Krylov subspace method" xsd:string {comment="EXACT"}
-property_value: definition "Krylov subspace method is an iterative linear equation method, which builds up Krylov subspaces and look for good approximations to eigenvectors and invariant subspaces within the Krylov spaces." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000398 ! iterative method for solving a system of linear equations
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/0898715342" xsd:anyURI {comment="Y. Saad. 2003. Iterative Methods for Sparse Linear Systems (2nd ed.). Soc. for Industrial and Applied Math., Philadelphia, PA, USA."}
+property_value: skos:altLabel "Krylov subspace method" xsd:string {comment="EXACT"}
+property_value: skos:definition "Krylov subspace method is an iterative linear equation method, which builds up Krylov subspaces and look for good approximations to eigenvectors and invariant subspaces within the Krylov spaces." xsd:string
 
 [Term]
-id: KISAO_0000355
+id: kisao:KISAO_0000355
 name: DASPK
-is_a: KISAO_0000432 ! IDA-like method
-relationship: KISAO_0000359 KISAO_0000283 ! IDA
-relationship: KISAO_0000360 KISAO_0000353 ! generalized minimal residual algorithm
-relationship: KISAO_0000360 KISAO_0000356 ! DASSL
-relationship: KISAO_0000360 KISAO_0000386 ! scaled preconditioned generalized minimal residual method
-property_value: altLabel "DDASPK" xsd:string {comment="NARROW"}
-property_value: altLabel "differential algebraic system solver with Krylov preconditioning" xsd:string {comment="EXACT"}
-property_value: altLabel "SDASPK" xsd:string {comment="NARROW"}
-property_value: definition "In DASPK, we have combined the time-stepping methods of DASSL [http://identifiers.org/biomodels.kisao/KISAO_0000255] with preconditioned iterative method GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000386], for solving large-scale systems of DAEs of the form F(t, y, y') = 0, where F, y, y' are N-dimensional vectors, and a consistent set of initial conditions y(t0) = y0, y'(t0) = y'0 is given.\nDASPK is written in Fortran." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000432 ! IDA-like method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000373 ! differential-algebraic equation problem
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000283 ! IDA
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000353 ! generalized minimal residual algorithm
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000356 ! DASSL
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000386 ! scaled preconditioned generalized minimal residual method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0915088" xsd:anyURI {comment="Peter N. Brown, Alan C. Hindmarsh, and Linda R. Petzold. 1994. Using Krylov methods in the solution of large-scale differential-algebraic systems. SIAM J. Sci. Comput. 15, 6 (November 1994), 1467-1488."}
+property_value: skos:altLabel "DDASPK" xsd:string {comment="NARROW"}
+property_value: skos:altLabel "differential algebraic system solver with Krylov preconditioning" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "SDASPK" xsd:string {comment="NARROW"}
+property_value: skos:definition "In DASPK, we have combined the time-stepping methods of DASSL [http://identifiers.org/biomodels.kisao/KISAO_0000255] with preconditioned iterative method GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000386], for solving large-scale systems of DAEs of the form F(t, y, y') = 0, where F, y, y' are N-dimensional vectors, and a consistent set of initial conditions y(t0) = y0, y'(t0) = y'0 is given.\nDASPK is written in Fortran." xsd:string
 
 [Term]
-id: KISAO_0000356
+id: kisao:KISAO_0000356
 name: DASSL
-is_a: KISAO_0000432 ! IDA-like method
-property_value: altLabel "DDASSL" xsd:string {comment="NARROW"}
-property_value: altLabel "differential algebraic system solver" xsd:string {comment="EXACT"}
-property_value: altLabel "SDASSL" xsd:string {comment="NARROW"}
-property_value: definition "DASSL is designed for the numerical solution of implicit systems of differential/algebraic equations written in the form F(t,y,y')=0, where F, y, and y' are vectors, and initial values for y and y' are given." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000432 ! IDA-like method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000373 ! differential-algebraic equation problem
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://www.nea.fr/abs/html/nesc9918.html" xsd:anyURI {comment="Linda R. Petzold: A Description of DASSL: A Differential/Algebraic System Solver, SAND82-8637 (September 1982)."}
+property_value: skos:altLabel "DDASSL" xsd:string {comment="NARROW"}
+property_value: skos:altLabel "differential algebraic system solver" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "SDASSL" xsd:string {comment="NARROW"}
+property_value: skos:definition "DASSL is designed for the numerical solution of implicit systems of differential/algebraic equations written in the form F(t,y,y')=0, where F, y, and y' are vectors, and initial values for y and y' are given." xsd:string
 
 [Term]
-id: KISAO_0000357
+id: kisao:KISAO_0000357
 name: conjugate gradient method
-is_a: KISAO_0000354 ! Krylov subspace projection method
-property_value: altLabel "CG" xsd:string {comment="EXACT"}
-property_value: definition "Conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is symmetric and positive-definite. The conjugate gradient method is an iterative method, so it can be applied to sparse systems that are too large to be handled by direct methods. Such systems often arise when numerically solving partial differential equations." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000354 ! Krylov subspace projection method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000404 ! symmetricity of matrix
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "urn:issn:0091-0635" xsd:anyURI {comment="M. R. Hestenes and E. L. Stiefel, Methods of conjugate gradients for solving linear systems. J. Res. Natl. Bur. Stand. 49 (1952), p. 409."}
+property_value: skos:altLabel "CG" xsd:string {comment="EXACT"}
+property_value: skos:definition "Conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is symmetric and positive-definite. The conjugate gradient method is an iterative method, so it can be applied to sparse systems that are too large to be handled by direct methods. Such systems often arise when numerically solving partial differential equations." xsd:string
 
 [Term]
-id: KISAO_0000358
+id: kisao:KISAO_0000358
 name: biconjugate gradient method
-is_a: KISAO_0000354 ! Krylov subspace projection method
-relationship: KISAO_0000361 KISAO_0000357 ! conjugate gradient method
-property_value: altLabel "BCG" xsd:string {comment="EXACT"}
-property_value: altLabel "Bi-CG" xsd:string {comment="EXACT"}
-property_value: altLabel "BiCG" xsd:string {comment="EXACT"}
-property_value: definition "The biconjugate gradient method provides a generalization of conjugate gradient method [http://identifiers.org/biomodels.kisao/KISAO_0000357] to non-symmetric matrices." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000354 ! Krylov subspace projection method
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000357 ! conjugate gradient method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1007/BFb0080109" xsd:anyURI {comment="Fletcher, R. (1976). \"Conjugate gradient methods for indefinite systems\". Numerical Analysis. Lecture Notes in Mathematics (Springer Berlin / Heidelberg) 506: 73-89."}
+property_value: skos:altLabel "BCG" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Bi-CG" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "BiCG" xsd:string {comment="EXACT"}
+property_value: skos:definition "The biconjugate gradient method provides a generalization of conjugate gradient method [http://identifiers.org/biomodels.kisao/KISAO_0000357] to non-symmetric matrices." xsd:string
 
 [Term]
-id: KISAO_0000362
+id: kisao:KISAO_0000362
 name: implicit-state Doob-Gillespie algorithm
-is_a: KISAO_0000017 ! multi-state agent-based simulation method
-relationship: KISAO_0000359 KISAO_0000021 ! StochSim nearest-neighbour algorithm
-relationship: KISAO_0000361 KISAO_0000029 ! Gillespie direct algorithm
-property_value: definition "The algorithm uses a representation of the system together with a super-approximation of its ‘event horizon’ (all events that may happen next), and a specific correction scheme to obtain exact timings. Being completely local and not based on any kind of enumeration, this algorithm has a per event time cost which is independent of (i) the size of the set of generable species (which can even be infinite), and (ii) independent of the size of the system (ie, the number of agent instances). The algorithm can be refined, using concepts derived from the classical notion of causality, so that in addition to the above one also has that the even cost is depending (iii) only logarithmically on the size of the model (ie, the number of rules).\n" xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000017 ! multi-state agent-based simulation method
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000021 ! StochSim nearest-neighbour algorithm
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000029 ! Gillespie direct algorithm
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/3-540-76636-7 978-3-540-76636-0" xsd:anyURI {comment="V. Danos, J. Feret, W. Fontana, and J. Krivine. 2007. Scalable simulation of cellular signalling networks. In Proceedings of the 5th Asian conference on Programming languages and systems (APLAS'07), Zhong Shao (Ed.). Springer-Verlag, Berlin, Heidelberg, 139-157."}
+property_value: skos:definition "The algorithm uses a representation of the system together with a super-approximation of its ‘event horizon’ (all events that may happen next), and a specific correction scheme to obtain exact timings. Being completely local and not based on any kind of enumeration, this algorithm has a per event time cost which is independent of (i) the size of the set of generable species (which can even be infinite), and (ii) independent of the size of the system (ie, the number of agent instances). The algorithm can be refined, using concepts derived from the classical notion of causality, so that in addition to the above one also has that the even cost is depending (iii) only logarithmically on the size of the model (ie, the number of rules).\n" xsd:string
 
 [Term]
-id: KISAO_0000363
+id: kisao:KISAO_0000363
 name: rule-based simulation method
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: definition "Rule-based models provide a powerful alternative to approaches that require explicit enumeration of all possible molecular species of a system. Such models consist of formal rules governing interactive behaviour. Rule-based simulation methods simulate such models." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000105 ! discrete variable
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Rule-based models provide a powerful alternative to approaches that require explicit enumeration of all possible molecular species of a system. Such models consist of formal rules governing interactive behaviour. Rule-based simulation methods simulate such models." xsd:string
 
 [Term]
-id: KISAO_0000364
+id: kisao:KISAO_0000364
 name: Adams predictor-corrector method
-is_a: KISAO_0000289 ! Adams method
-relationship: KISAO_0000360 KISAO_0000279 ! Adams-Bashforth method
-relationship: KISAO_0000360 KISAO_0000280 ! Adams-Moulton method
-property_value: definition "The combination of evaluating a single explicit integration method ('Adams-Bashforth method' [http://identifiers.org/biomodels.kisao/KISAO_0000279]) (the predictor step) in order to provide a good initial guess for the successive evaluation of an implicit method ('Adams-Moulton method' [http://identifiers.org/biomodels.kisao/KISAO_0000280]) (the corrector step) using iteration." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "GSL" xsd:string
+is_a: kisao:KISAO_0000289 ! Adams method
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000279 ! Adams-Bashforth method
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000280 ! Adams-Moulton method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "GSL" xsd:string
 property_value: seeAlso "urn:asin:B0000EFQ8B" xsd:anyURI {comment="Moulton, Forest R. (1926), New methods in exterior ballistics, University of Chicago Press."}
+property_value: skos:definition "The combination of evaluating a single explicit integration method ('Adams-Bashforth method' [http://identifiers.org/biomodels.kisao/KISAO_0000279]) (the predictor step) in order to provide a good initial guess for the successive evaluation of an implicit method ('Adams-Moulton method' [http://identifiers.org/biomodels.kisao/KISAO_0000280]) (the corrector step) using iteration." xsd:string
 
 [Term]
-id: KISAO_0000365
+id: kisao:KISAO_0000365
 name: NDSolve method
-is_a: KISAO_0000352 ! hybrid method
-relationship: KISAO_0000246 KISAO_0000288 ! backward differentiation formula
-relationship: KISAO_0000246 KISAO_0000302 ! embedded Runge-Kutta method
-relationship: KISAO_0000246 KISAO_0000310 ! method of lines
-relationship: KISAO_0000246 KISAO_0000364 ! Adams predictor-corrector method
-relationship: KISAO_0000246 KISAO_0000367 ! partitioned Runge-Kutta method
-property_value: definition "The Mathematica computation system function NDSolve is a general numerical differential equation solver. It can handle a wide range of ordinary differential equations as well as some partial differential equations. NDSolve can also solve some differential-algebraic equations, which are typically a mix of differential and algebraic equations." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "Mathematica" xsd:string
+is_a: kisao:KISAO_0000352 ! hybrid method
+relationship: kisao:KISAO_0000246 kisao:KISAO_0000288 ! backward differentiation formula
+relationship: kisao:KISAO_0000246 kisao:KISAO_0000302 ! embedded Runge-Kutta method
+relationship: kisao:KISAO_0000246 kisao:KISAO_0000310 ! method of lines
+relationship: kisao:KISAO_0000246 kisao:KISAO_0000364 ! Adams predictor-corrector method
+relationship: kisao:KISAO_0000246 kisao:KISAO_0000367 ! partitioned Runge-Kutta method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "Mathematica" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/978-1-57955-058-5" xsd:anyURI {comment="Advanced Numerical Differential Equation Solving in Mathematica, Wolfram Mathematica Tutorial Collection, 2008."}
+property_value: skos:definition "The Mathematica computation system function NDSolve is a general numerical differential equation solver. It can handle a wide range of ordinary differential equations as well as some partial differential equations. NDSolve can also solve some differential-algebraic equations, which are typically a mix of differential and algebraic equations." xsd:string
+
+[Term]
+id: kisao:KISAO_0000366
+name: symplecticness
+is_a: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+property_value: dc:creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1017/S0962492900002282" xsd:anyURI {comment=" J. M. Sanz-Serna (1992). Symplectic integrators for Hamiltonian problems: an overview. Acta Numerica, 1, pp 243-286"}
+property_value: skos:definition "Roughly speaking, ‘symplecticness’ is a characteristic property possessed by the solutions of Hamiltonian problems. A numerical method is called symplectic if, when applied to Hamiltonian problems, it generates numerical solutions which inherit the property of symplecticness (phase volume preservation)." xsd:string
 
 [Term]
-id: KISAO_0000367
+id: kisao:KISAO_0000367
 name: partitioned Runge-Kutta method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-relationship: KISAO_0000360 KISAO_0000064 {minCardinality="2"} ! Runge-Kutta based method
-property_value: altLabel "PRK" xsd:string {comment="EXACT"}
-property_value: altLabel "SPRK" xsd:string {comment="EXACT"}
-property_value: altLabel "symplectic partitioned Runge-Kutta method" xsd:string {comment="EXACT"}
-property_value: definition "If a Hamiltonian system possesses a natural partitioning, it is possible to integrate its certain components using one Runge-Kutta method and other components using a different Runge-Kutta method. The overall s-stage scheme is called a partitioned Runge-Kutta method." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000366 ! symplecticness
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000064 {minCardinality="2"} ! Runge-Kutta based method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1007/BF01389456" xsd:anyURI {comment="P. Rentrop (1985): Partitioned Runge-Kutta methods with stiffness detection and stepsize control. Numer. Math., Vol. 47, p.545-564."}
+property_value: skos:altLabel "PRK" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "SPRK" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "symplectic partitioned Runge-Kutta method" xsd:string {comment="EXACT"}
+property_value: skos:definition "If a Hamiltonian system possesses a natural partitioning, it is possible to integrate its certain components using one Runge-Kutta method and other components using a different Runge-Kutta method. The overall s-stage scheme is called a partitioned Runge-Kutta method." xsd:string
 
 [Term]
-id: KISAO_0000369
+id: kisao:KISAO_0000369
 name: partial differential equation discretization method
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: definition "A method which solves partial differential equations by discretizing them, i.e. approximating them by equations that involve a finite number of unknowns." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000102 ! spatial description
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000372 ! partial differential equation problem
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A method which solves partial differential equations by discretizing them, i.e. approximating them by equations that involve a finite number of unknowns." xsd:string
 
 [Term]
-id: KISAO_0000377
+id: kisao:KISAO_0000370
+name: type of problem
+is_a: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A characteristic describing the type of the problems which can be solved by the algorithm." xsd:string
+
+[Term]
+id: kisao:KISAO_0000371
+name: stochastic differential equation problem
+is_a: kisao:KISAO_0000405 ! type of differential equation
+disjoint_from: kisao:KISAO_0000372 ! partial differential equation problem
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:altLabel "SDE problem" xsd:string {comment="EXACT"}
+
+[Term]
+id: kisao:KISAO_0000372
+name: partial differential equation problem
+is_a: kisao:KISAO_0000405 ! type of differential equation
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:altLabel "PDE problem" xsd:string {comment="EXACT"}
+
+[Term]
+id: kisao:KISAO_0000373
+name: differential-algebraic equation problem
+is_a: kisao:KISAO_0000405 ! type of differential equation
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:altLabel "DAE" xsd:string {comment="EXACT"}
+
+[Term]
+id: kisao:KISAO_0000374
+name: ordinary differential equation problem
+is_a: kisao:KISAO_0000405 ! type of differential equation
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:altLabel "ODE problem" xsd:string {comment="EXACT"}
+
+[Term]
+id: kisao:KISAO_0000375
+name: delay differential equation problem
+is_a: kisao:KISAO_0000405 ! type of differential equation
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:altLabel "DDE problem" xsd:string
+
+[Term]
+id: kisao:KISAO_0000376
+name: linearity of equation
+is_a: kisao:KISAO_0000370 ! type of problem
+disjoint_from: kisao:KISAO_0000404 ! symmetricity of matrix
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "Linear differential equations are of the form Ly = f, where the differential operator L is a linear operator, y is the unknown function, and the right hand side f is a given function of the same nature as y." xsd:string
+
+[Term]
+id: kisao:KISAO_0000377
 name: one-step method
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: definition "A numerical method for differential equations which uses one starting value at each step." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000694 ! ODE solver
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000483 ! step size
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+property_value: skos:definition "A numerical method for differential equations which uses one starting value at each step." xsd:string
 
 [Term]
-id: KISAO_0000378
+id: kisao:KISAO_0000378
 name: implicit midpoint rule
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: altLabel "implicit Gaussian second order Runge-Kutta method" xsd:string {comment="EXACT"}
-property_value: definition "The implicit midpoint rule is a second-order case of the more general implicit s-stage Runge-Kutta methods [http://identifiers.org/biomodels.kisao/KISAO_0000064 and (http://identifiers.org/biomodels.kisao/KISAO_0000245 some http://identifiers.org/biomodels.kisao/KISAO_0000240)]." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "GSL" xsd:string
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "GSL" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag."}
+property_value: skos:altLabel "implicit Gaussian second order Runge-Kutta method" xsd:string {comment="EXACT"}
+property_value: skos:definition "The implicit midpoint rule is a second-order case of the more general implicit s-stage Runge-Kutta methods [http://identifiers.org/biomodels.kisao/KISAO_0000064 and (http://identifiers.org/biomodels.kisao/KISAO_0000245 some http://identifiers.org/biomodels.kisao/KISAO_0000240)]." xsd:string
 
 [Term]
-id: KISAO_0000379
+id: kisao:KISAO_0000379
 name: Bulirsch-Stoer algorithm
-is_a: KISAO_0000380 ! Richardson extrapolation based method
-relationship: KISAO_0000360 KISAO_0000382 ! modified midpoint method
-property_value: altLabel "GBS" xsd:string {comment="EXACT"}
-property_value: altLabel "Gragg-Bulirsch-Stoer algorithm" xsd:string {comment="EXACT"}
-property_value: definition "The Bulirsch-Stoer method is an adaptive method which uses Gragg's modified midpoint method [http://identifiers.org/biomodels.kisao/KISAO_0000382] to estimate the solution of an initial value problem for various step sizes. The estimates are fit to a \"diagonal\" rational function or a polynomial as a function of the step size and the limit as the step size tends to zero is taken as the final estimate." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000380 ! Richardson extrapolation based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000382 ! modified midpoint method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1007/BF02165234" xsd:anyURI {comment="Bulirsch R. and Stoer J. (1966) Numerical treatment of ordinary differential equations by extrapolation methods, Numerische Mathematik, Volume 8, Number 1, 1-13."}
+property_value: skos:altLabel "GBS" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Gragg-Bulirsch-Stoer algorithm" xsd:string {comment="EXACT"}
+property_value: skos:definition "The Bulirsch-Stoer method is an adaptive method which uses Gragg's modified midpoint method [http://identifiers.org/biomodels.kisao/KISAO_0000382] to estimate the solution of an initial value problem for various step sizes. The estimates are fit to a \"diagonal\" rational function or a polynomial as a function of the step size and the limit as the step size tends to zero is taken as the final estimate." xsd:string
 
 [Term]
-id: KISAO_0000380
+id: kisao:KISAO_0000380
 name: Richardson extrapolation based method
-is_a: KISAO_0000377 ! one-step method
-property_value: definition "A method based on ideas of Richardson extrapolation, which is a process for obtaining increased accuracy in a discretized approximation by extrapolating results from coarse discretizations to an arbitrarily fine one." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000377 ! one-step method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://identifiers.org/doi/10.1098/rsta.1911.0009" xsd:anyURI {comment="Richardson, L. F. (1911). The approximate arithmetical solution by finite differences of physical problems including differential equations, with an application to the stresses in a masonry dam. Philosophical Transactions of the Royal Society of London, Series A 210 (459-470): 307-357."}
+property_value: skos:definition "A method based on ideas of Richardson extrapolation, which is a process for obtaining increased accuracy in a discretized approximation by extrapolating results from coarse discretizations to an arbitrarily fine one." xsd:string
 
 [Term]
-id: KISAO_0000381
+id: kisao:KISAO_0000381
 name: midpoint method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: definition "The midpoint method is an explicit method for approximating the solution of the initial value problem y' = f(x,y);  y(x0) = y0 at x for a given step size h. For the midpoint method the derivative of y(x) is approximated by the symmetric difference y'(x) = ( y(x+h) - y(x-h) ) / 2h + O(h2)." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000239 ! explicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag."}
+property_value: skos:definition "The midpoint method is an explicit method for approximating the solution of the initial value problem y' = f(x,y);  y(x0) = y0 at x for a given step size h. For the midpoint method the derivative of y(x) is approximated by the symmetric difference y'(x) = ( y(x+h) - y(x-h) ) / 2h + O(h2)." xsd:string
 
 [Term]
-id: KISAO_0000382
+id: kisao:KISAO_0000382
 name: modified midpoint method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: altLabel "Gragg's method" xsd:string {comment="EXACT"}
-property_value: altLabel "Gragg's modified midpoint method" xsd:string
-property_value: definition "The modified midpoint method is globally a second order method for approximating the solution of the initial value problem y' = f(x, y), y(x0) = y0, which advances a vector of dependent variables y(x) from a point x to a point x + H by a sequence of n substeps each of size h, h = H/n.\n" xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000239 ! explicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/052143064X" xsd:anyURI {comment="Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical Recipes in Fortran 77. Cambridge University Press (2001)."}
+property_value: skos:altLabel "Gragg's method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Gragg's modified midpoint method" xsd:string
+property_value: skos:definition "The modified midpoint method is globally a second order method for approximating the solution of the initial value problem y' = f(x, y), y(x0) = y0, which advances a vector of dependent variables y(x) from a point x to a point x + H by a sequence of n substeps each of size h, h = H/n.\n" xsd:string
 
 [Term]
-id: KISAO_0000383
+id: kisao:KISAO_0000383
 name: Bader-Deuflhard method
-is_a: KISAO_0000380 ! Richardson extrapolation based method
-relationship: KISAO_0000360 KISAO_0000384 ! semi-implicit midpoint rule
-relationship: KISAO_0000361 KISAO_0000379 ! Bulirsch-Stoer algorithm
-property_value: definition "The Bader-Deuflhard method is an extrapolation method based on a semi-implicit discretization [http://identifiers.org/biomodels.kisao/KISAO_0000387]. It is a generalization of the Bulirsch-Stoer algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000379] for solving ordinary differential equations." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "GSL" xsd:string
+is_a: kisao:KISAO_0000380 ! Richardson extrapolation based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000384 ! semi-implicit midpoint rule
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000379 ! Bulirsch-Stoer algorithm
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "GSL" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1007/BF01418331" xsd:anyURI {comment="Bader, G. and Deuflhard, P. \"A Semi-Implicit Mid-Point Rule for Stiff Systems of Ordinary Differential Equations.\" Numer. Math. 41, 373-398, 1983."}
+property_value: skos:definition "The Bader-Deuflhard method is an extrapolation method based on a semi-implicit discretization [http://identifiers.org/biomodels.kisao/KISAO_0000387]. It is a generalization of the Bulirsch-Stoer algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000379] for solving ordinary differential equations." xsd:string
 
 [Term]
-id: KISAO_0000384
+id: kisao:KISAO_0000384
 name: semi-implicit midpoint rule
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: definition "A semi-implicit version of the midpoint method that has an even error series [http://identifiers.org/biomodels.kisao/KISAO_0000381]." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000240 ! implicit method type
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1007/BF01418331" xsd:anyURI {comment="Bader, G. and Deuflhard, P. \"A Semi-Implicit Mid-Point Rule for Stiff Systems of Ordinary Differential Equations.\" Numer. Math. 41, 373-398, 1983."}
+property_value: skos:definition "A semi-implicit version of the midpoint method that has an even error series [http://identifiers.org/biomodels.kisao/KISAO_0000381]." xsd:string
 
 [Term]
-id: KISAO_0000386
+id: kisao:KISAO_0000386
 name: scaled preconditioned generalized minimal residual method
-is_a: KISAO_0000353 ! generalized minimal residual algorithm
-relationship: KISAO_0000360 KISAO_0000397 ! preconditioning technique
-property_value: altLabel "SPGMR" xsd:string {comment="EXACT"}
-property_value: definition "A scaled preconditioned version of 'generalized minimal residual algorithm' [http://identifiers.org/biomodels.kisao/KISAO_0000353]. For linear system Ax = b a preconditioner matrix P that approximates A is sought, for which linear system Px = b can be solved easily. Preconditioning is applied on the left only. Scaling is done using diagonal matrix D whose diagonal elements are weights w^i = rtol|y^i| +atol^i, where rtol is 'relative tolerance' [http://identifiers.org/biomodels.kisao/KISAO_0000209] and atol is 'absolute tolerance' [http://identifiers.org/biomodels.kisao/KISAO_0000211]." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000353 ! generalized minimal residual algorithm
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000397 ! preconditioning technique
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0915088" xsd:anyURI {comment="Peter N. Brown, Alan C. Hindmarsh, and Linda R. Petzold. 1994. Using Krylov methods in the solution of large-scale differential-algebraic systems. SIAM J. Sci. Comput. 15, 6 (November 1994), 1467-1488."}
+property_value: skos:altLabel "SPGMR" xsd:string {comment="EXACT"}
+property_value: skos:definition "A scaled preconditioned version of 'generalized minimal residual algorithm' [http://identifiers.org/biomodels.kisao/KISAO_0000353]. For linear system Ax = b a preconditioner matrix P that approximates A is sought, for which linear system Px = b can be solved easily. Preconditioning is applied on the left only. Scaling is done using diagonal matrix D whose diagonal elements are weights w^i = rtol|y^i| +atol^i, where rtol is 'relative tolerance' [http://identifiers.org/biomodels.kisao/KISAO_0000209] and atol is 'absolute tolerance' [http://identifiers.org/biomodels.kisao/KISAO_0000211]." xsd:string
 
 [Term]
-id: KISAO_0000388
+id: kisao:KISAO_0000388
 name: minimal residual method
-is_a: KISAO_0000354 ! Krylov subspace projection method
-property_value: altLabel "MINRES" xsd:string {comment="EXACT"}
-property_value: definition "The 'minimal residual method' is an algorithm for the numerical solution of indefinite symmertic systems of linear equations." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000354 ! Krylov subspace projection method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000404 ! symmetricity of matrix
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0712047" xsd:anyURI {comment="Paige C.C., Saunders M.A. Solution of sparse indefinite systems of linear equations, SIAM Journal on Numerical Analysis (1975) Volume: 12, Issue: 4, Publisher: SIAM, Pages: 617-629."}
+property_value: skos:altLabel "MINRES" xsd:string {comment="EXACT"}
+property_value: skos:definition "The 'minimal residual method' is an algorithm for the numerical solution of indefinite symmertic systems of linear equations." xsd:string
 
 [Term]
-id: KISAO_0000389
+id: kisao:KISAO_0000389
 name: quasi-minimal residual method
-is_a: KISAO_0000393 ! ingenious conjugate gradients-squared method
-property_value: altLabel "QMR" xsd:string {comment="EXACT"}
-property_value: definition "The QMR algorithm is a robust iterative solver for general nonsingular non-Hermitian linear systems. The method uses a robust implementation of the look-ahead Lanczos algorithm to generate basis vectors for the Krylov subspaces Kn(r0, A). The QMR iterates are characterized by a quasi-minimal residual property over Kn(r0, A)." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000393 ! ingenious conjugate gradients-squared method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1007/BF01385726" xsd:anyURI {comment="Roland W. Freund and Noël M. Nachtigal. QMR: a quasi-minimal residual method for non-Hermitian linear systems. NUMERISCHE MATHEMATIK Volume 60, Number 1, 315-339.\n"}
+property_value: skos:altLabel "QMR" xsd:string {comment="EXACT"}
+property_value: skos:definition "The QMR algorithm is a robust iterative solver for general nonsingular non-Hermitian linear systems. The method uses a robust implementation of the look-ahead Lanczos algorithm to generate basis vectors for the Krylov subspaces Kn(r0, A). The QMR iterates are characterized by a quasi-minimal residual property over Kn(r0, A)." xsd:string
 
 [Term]
-id: KISAO_0000392
+id: kisao:KISAO_0000392
 name: biconjugate gradient stabilized method
-is_a: KISAO_0000395 ! improved biconjugate gradient method
-disjoint_from: KISAO_0000393 ! ingenious conjugate gradients-squared method
-property_value: altLabel "Bi-CGSTAB" xsd:string {comment="EXACT"}
-property_value: altLabel "BiCGSTAB" xsd:string {comment="EXACT"}
-property_value: definition "An iterative method for the numerical solution of nonsymmetric linear systems. It is a variant of the biconjugate gradient method (BiCG) [http://identifiers.org/biomodels.kisao/KISAO_0000358] and has faster and smoother convergence than the original BiCG." xsd:string
-property_value: isImplementedIn "CVODE" xsd:string
+is_a: kisao:KISAO_0000395 ! improved biconjugate gradient method
+disjoint_from: kisao:KISAO_0000393 ! ingenious conjugate gradients-squared method
+property_value: kisao:isImplementedIn "CVODE" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0913035" xsd:anyURI {comment="Van der Vorst, H. A. (1992). Bi-CGSTAB: A Fast and Smoothly Converging Variant of Bi-CG for the Solution of Nonsymmetric Linear Systems. SIAM Journal on Scientific and Statistical Computing 13: 631-644."}
+property_value: skos:altLabel "Bi-CGSTAB" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "BiCGSTAB" xsd:string {comment="EXACT"}
+property_value: skos:definition "An iterative method for the numerical solution of nonsymmetric linear systems. It is a variant of the biconjugate gradient method (BiCG) [http://identifiers.org/biomodels.kisao/KISAO_0000358] and has faster and smoother convergence than the original BiCG." xsd:string
 
 [Term]
-id: KISAO_0000393
+id: kisao:KISAO_0000393
 name: ingenious conjugate gradients-squared method
-is_a: KISAO_0000395 ! improved biconjugate gradient method
-property_value: altLabel "CGS" xsd:string {comment="EXACT"}
-property_value: definition "A Lanczos-type method for nonsymmetric sparse linear systems. The method is based on a polynomial variant of the conjugate gradients algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000357]. Although related to the so-called bi-conjugate gradients (Bi-CG) algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000358], it does not involve adjoint matrix-vector multiplications, and the expected convergence rate is about twice that of the Bi-CG algorithm." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000395 ! improved biconjugate gradient method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0910004" xsd:anyURI {comment="Peter Sonneveld. 1989. CGS, a fast Lanczos-type solver for nonsymmetric linear systems. SIAM J. Sci. Stat. Comput. 10, 1 (January 1989), 36-52."}
+property_value: skos:altLabel "CGS" xsd:string {comment="EXACT"}
+property_value: skos:definition "A Lanczos-type method for nonsymmetric sparse linear systems. The method is based on a polynomial variant of the conjugate gradients algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000357]. Although related to the so-called bi-conjugate gradients (Bi-CG) algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000358], it does not involve adjoint matrix-vector multiplications, and the expected convergence rate is about twice that of the Bi-CG algorithm." xsd:string
 
 [Term]
-id: KISAO_0000394
+id: kisao:KISAO_0000394
 name: quasi-minimal residual variant of biconjugate gradient stabilized method
-is_a: KISAO_0000392 ! biconjugate gradient stabilized method
-property_value: altLabel "QMRCGSTAB" xsd:string {comment="EXACT"}
-property_value: definition "QMRCGSTAB is a quasi-minimal residual (QMR) variant of the Bi-CGSTAB algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000394] of van der Vorst for solving nonsymmetric linear systems. The motivation for the QMR variant is to obtain smoother convergence behavior of the underlying method.\n" xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000392 ! biconjugate gradient stabilized method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0915023" xsd:anyURI {comment="T. F. Chan, E. Gallopoulos, V. Simoncini, T. Szeto, and C. H. Tong. 1994. A quasi-minimal residual variant of the Bi-CGSTAB algorithm for nonsymmetric systems. SIAM J. Sci. Comput. 15, 2 (March 1994), 338-347."}
+property_value: skos:altLabel "QMRCGSTAB" xsd:string {comment="EXACT"}
+property_value: skos:definition "QMRCGSTAB is a quasi-minimal residual (QMR) variant of the Bi-CGSTAB algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000394] of van der Vorst for solving nonsymmetric linear systems. The motivation for the QMR variant is to obtain smoother convergence behavior of the underlying method.\n" xsd:string
 
 [Term]
-id: KISAO_0000395
+id: kisao:KISAO_0000395
 name: improved biconjugate gradient method
-is_a: KISAO_0000354 ! Krylov subspace projection method
-relationship: KISAO_0000359 KISAO_0000358 ! biconjugate gradient method
-property_value: definition "An 'improved biconjugate gradient method' branch contains algorithms which can be viewed as improvements over some of drawbacks of BCG [http://identifiers.org/biomodels.kisao/KISAO_0000358], such as (1) the need for matrix-vector multiplications with A^T (which can be inconvenient as well as doubling the number of matrix-vector multiplications compared to CG [http://identifiers.org/biomodels.kisao/KISAO_0000357] for each increase in the degree of the underlying Krylov subspace), (2) the possibility of breakdowns and (3) erratic convergence behavior.\n" xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000354 ! Krylov subspace projection method
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000358 ! biconjugate gradient method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "An 'improved biconjugate gradient method' branch contains algorithms which can be viewed as improvements over some of drawbacks of BCG [http://identifiers.org/biomodels.kisao/KISAO_0000358], such as (1) the need for matrix-vector multiplications with A^T (which can be inconvenient as well as doubling the number of matrix-vector multiplications compared to CG [http://identifiers.org/biomodels.kisao/KISAO_0000357] for each increase in the degree of the underlying Krylov subspace), (2) the possibility of breakdowns and (3) erratic convergence behavior.\n" xsd:string
 
 [Term]
-id: KISAO_0000396
+id: kisao:KISAO_0000396
 name: transpose-free quasi-minimal residual algorithm
-is_a: KISAO_0000389 ! quasi-minimal residual method
-property_value: altLabel "TFQMR" xsd:string {comment="EXACT"}
-property_value: definition "A version of CGS [http://identifiers.org/biomodels.kisao/KISAO_0000393] which 'quasi-minimizes' the residual in the space spanned by the vectors generated by the CGS iteration.\n" xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "CVODE" xsd:string
+is_a: kisao:KISAO_0000389 ! quasi-minimal residual method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "CVODE" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0914029" xsd:anyURI {comment="Roland W. Freund. 1993. A transpose-free quasi-minimal residual algorithm for non-Hermitian linear systems. SIAM J. Sci. Comput. 14, 2 (March 1993), 470-482."}
+property_value: skos:altLabel "TFQMR" xsd:string {comment="EXACT"}
+property_value: skos:definition "A version of CGS [http://identifiers.org/biomodels.kisao/KISAO_0000393] which 'quasi-minimizes' the residual in the space spanned by the vectors generated by the CGS iteration.\n" xsd:string
 
 [Term]
-id: KISAO_0000397
+id: kisao:KISAO_0000397
 name: preconditioning technique
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-relationship: KISAO_0000399 KISAO_0000398 ! iterative method for solving a system of linear equations
-property_value: definition "Preconditioning is simply a means of transforming the original linear system into one which has the same solution, but which is likely to be easier to solve with an iterative solver." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000399 kisao:KISAO_0000398 ! iterative method for solving a system of linear equations
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/0898715342" xsd:anyURI {comment="Saad, Yousef (2003). Iterative methods for sparse linear systems (2nd ed.). SIAM."}
+property_value: skos:definition "Preconditioning is simply a means of transforming the original linear system into one which has the same solution, but which is likely to be easier to solve with an iterative solver." xsd:string
 
 [Term]
-id: KISAO_0000398
+id: kisao:KISAO_0000398
 name: iterative method for solving a system of linear equations
-is_a: KISAO_0000624 ! method for solving a system of linear equations
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000624 ! method for solving a system of linear equations
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://identifiers.org/isbn/0898715342" xsd:anyURI {comment="Saad, Yousef (2003). Iterative methods for sparse linear systems (2nd ed.). SIAM."}
 
 [Term]
-id: KISAO_0000407
-name: steady state method
+id: kisao:KISAO_0000403
+name: homogeneousness of equation
+is_a: kisao:KISAO_0000376 ! linearity of equation
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "Homogeneous equations are of the form Ly = 0, where the differential operator L is a linear operator and y is the unknown function." xsd:string
+
+[Term]
+id: kisao:KISAO_0000404
+name: symmetricity of matrix
+is_a: kisao:KISAO_0000370 ! type of problem
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "In linear algebra, a symmetric matrix is a square matrix that is equal to its transpose." xsd:string
+
+[Term]
+id: kisao:KISAO_0000405
+name: type of differential equation
+is_a: kisao:KISAO_0000370 ! type of problem
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+
+[Term]
+id: kisao:KISAO_0000407
+name: steady state root-finding method
 comment: Requested by Frank T. Bergmann on Sunday, November 27, 2011 4:45:30 PM.
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-is_a: KISAO_0000622 ! flux balance method
-property_value: definition "A method looking for a steady state of a dynamic system." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000630 ! general steady state method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000696 ! steady state root-finding problem
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "false" xsd:boolean
+property_value: skos:definition "Method for finding the root of a function (f(x) = 0)." xsd:string
 
 [Term]
-id: KISAO_0000408
+id: kisao:KISAO_0000408
 name: Newton-type method
 comment: Requested by Frank T. Bergmann on Sunday, November 27, 2011 4:45:30 PM.
-is_a: KISAO_0000631 ! iterative root-finding method
-property_value: definition "A method which attacks the solution of a nonlinear problem F(x) = 0 by solving a sequence of liner problems of the same kind.\nThe solution of the system F(x)=0 can be interpreted as a steady state of a dynamic system x'(t)=F(x(t)). The Newton approach will only work if the fixed point [http://identifiers.org/biomodels.teddy/TEDDY_0000086] of the dinamic system is attractive [http://identifiers.org/biomodels.teddy/TEDDY_0000094]." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000631 ! iterative root-finding method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000209 ! relative tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000211 ! absolute tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000415 ! maximum number of steps
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/9783540210993" xsd:anyURI {comment="Deuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms, Springer Series in Computational Mathematics, Vol. 35, 1st ed. 2004."}
+property_value: skos:definition "A method which attacks the solution of a nonlinear problem F(x) = 0 by solving a sequence of liner problems of the same kind.\nThe solution of the system F(x)=0 can be interpreted as a steady state of a dynamic system x'(t)=F(x(t)). The Newton approach will only work if the fixed point [http://identifiers.org/biomodels.teddy/TEDDY_0000086] of the dinamic system is attractive [http://identifiers.org/biomodels.teddy/TEDDY_0000094]." xsd:string
 
 [Term]
-id: KISAO_0000409
+id: kisao:KISAO_0000409
 name: ordinary Newton method
-is_a: KISAO_0000408 ! Newton-type method
-property_value: definition "A 'Newton-type method' [http://identifiers.org/biomodels.kisao/KISAO_0000408] which solves the general nonlinear problem F(x)=0 by applying successive linearization F'(x[k])deltax[k]=-F(x[k]), x[k+1]=x[k]+deltax[k], k=0,1,..." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000408 ! Newton-type method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/9783540210993" xsd:anyURI {comment="Deuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms, Springer Series in Computational Mathematics, Vol. 35, 1st ed. 2004."}
+property_value: skos:definition "A 'Newton-type method' [http://identifiers.org/biomodels.kisao/KISAO_0000408] which solves the general nonlinear problem F(x)=0 by applying successive linearization F'(x[k])deltax[k]=-F(x[k]), x[k+1]=x[k]+deltax[k], k=0,1,..." xsd:string
 
 [Term]
-id: KISAO_0000410
-name: simlified Newton method
-is_a: KISAO_0000408 ! Newton-type method
-property_value: definition "A 'Newton-type method' [http://identifiers.org/biomodels.kisao/KISAO_0000408] which is characterized by keeping the initial derivative throughout the whole iteration: F'(x[0])deltax[k]=-F(x[k]), x[k+1]=x[k]+deltax[k], k=0,1,..." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+id: kisao:KISAO_0000410
+name: simplified Newton method
+is_a: kisao:KISAO_0000408 ! Newton-type method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/9783540210993" xsd:anyURI {comment="Deuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms, Springer Series in Computational Mathematics, Vol. 35, 1st ed. 2004."}
+property_value: skos:definition "A 'Newton-type method' [http://identifiers.org/biomodels.kisao/KISAO_0000408] which is characterized by keeping the initial derivative throughout the whole iteration: F'(x[0])deltax[k]=-F(x[k]), x[k+1]=x[k]+deltax[k], k=0,1,..." xsd:string
 
 [Term]
-id: KISAO_0000411
+id: kisao:KISAO_0000411
 name: Newton-like method
-is_a: KISAO_0000408 ! Newton-type method
-property_value: definition "A 'Newton-type method' [http://identifiers.org/biomodels.kisao/KISAO_0000408] which is characterized by the fact that, in finite dimension, the Jacodian matrices are either replaced by some fixed 'close by' Jacobian F'(z) with z not equal to the initial guess x[0], or by some approximation so that: M'(x[0])deltax[k]=-F(x[k]), x[k+1]=x[k]+deltax[k], k=0,1,..." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000408 ! Newton-type method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/9783540210993" xsd:anyURI {comment="Deuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms, Springer Series in Computational Mathematics, Vol. 35, 1st ed. 2004."}
+property_value: skos:definition "A 'Newton-type method' [http://identifiers.org/biomodels.kisao/KISAO_0000408] which is characterized by the fact that, in finite dimension, the Jacodian matrices are either replaced by some fixed 'close by' Jacobian F'(z) with z not equal to the initial guess x[0], or by some approximation so that: M'(x[0])deltax[k]=-F(x[k]), x[k+1]=x[k]+deltax[k], k=0,1,..." xsd:string
 
 [Term]
-id: KISAO_0000412
+id: kisao:KISAO_0000412
 name: inexact Newton method
-is_a: KISAO_0000408 ! Newton-type method
-property_value: altLabel "iterative Newton method" xsd:string {comment="EXACT"}
-property_value: altLabel "truncated Newton method" xsd:string {comment="EXACT"}
-property_value: definition "For extremely large scale nonlinear problems the arising linear systems for the Newton corrections can no longer be solved directly ('exactly'), but must be solved iterativly ('inexactly) - which gives the name inexact Newton methods. The whole scheme then consists of an inner iteration (at Newton step k): \nF'(x[k])deltaxi[k]=-F(x[k])+ri[k], k=0,1,...\nxi[k+1]=x[k]+deltaxi[k], i=0,1,..,imax[k]\nin terms of residuals ri[k] and an outer iteration where, given x[0], the iterates are defined as x[k+1]=xi[k+1] for i=imax[k], k=0,1,..." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000408 ! Newton-type method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/9783540210993" xsd:anyURI {comment="Deuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms, Springer Series in Computational Mathematics, Vol. 35, 1st ed. 2004."}
+property_value: skos:altLabel "iterative Newton method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "truncated Newton method" xsd:string {comment="EXACT"}
+property_value: skos:definition "For extremely large scale nonlinear problems the arising linear systems for the Newton corrections can no longer be solved directly ('exactly'), but must be solved iterativly ('inexactly) - which gives the name inexact Newton methods. The whole scheme then consists of an inner iteration (at Newton step k): \nF'(x[k])deltaxi[k]=-F(x[k])+ri[k], k=0,1,...\nxi[k+1]=x[k]+deltaxi[k], i=0,1,..,imax[k]\nin terms of residuals ri[k] and an outer iteration where, given x[0], the iterates are defined as x[k+1]=xi[k+1] for i=imax[k], k=0,1,..." xsd:string
 
 [Term]
-id: KISAO_0000413
+id: kisao:KISAO_0000413
 name: exact Newton method
-is_a: KISAO_0000408 ! Newton-type method
-property_value: altLabel "direct Newton method" xsd:string
-property_value: definition "Any of the finite dimensional Newton-type methods [http://identifiers.org/biomodels.kisao/KISAO_0000408] requires the numerical solution of the linear equations F'(x[k])deltax[k]=-F(x[k]). Whenever direct elimination methods are applicable, we speak of exact Newton methods." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000408 ! Newton-type method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/9783540210993" xsd:anyURI {comment="Deuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms, Springer Series in Computational Mathematics, Vol. 35, 1st ed. 2004."}
+property_value: skos:altLabel "direct Newton method" xsd:string
+property_value: skos:definition "Any of the finite dimensional Newton-type methods [http://identifiers.org/biomodels.kisao/KISAO_0000408] requires the numerical solution of the linear equations F'(x[k])deltax[k]=-F(x[k]). Whenever direct elimination methods are applicable, we speak of exact Newton methods." xsd:string
+
+[Term]
+id: kisao:KISAO_0000415
+name: maximum number of steps
+is_a: kisao:KISAO_0000244 ! granularity control parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000408 {all_only="true"} ! Newton-type method
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:altLabel "maximum steps" xsd:string
+property_value: skos:definition "The limit on number of internal steps before an output point." xsd:string
 
 [Term]
-id: KISAO_0000416
+id: kisao:KISAO_0000416
 name: partial least squares regression method
 comment: Requested by Kristin Tøndel on Thursday, October 13, 2011 10:46:04 AM.
-is_a: KISAO_0000423 ! partial least squares regression-like method
-disjoint_from: KISAO_0000417 ! hierarchical cluster-based partial least squares regression method
-property_value: altLabel "PLSR" xsd:string {comment="EXACT"}
-property_value: altLabel "PLSR method" xsd:string {comment="EXACT"}
-property_value: definition "Multivariate regression method based on estimated latent variables. Related to Principal Component Analysis (PCA) and Principal Component Regression (PCR)." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000423 ! partial least squares regression-like method
+disjoint_from: kisao:KISAO_0000417 ! hierarchical cluster-based partial least squares regression method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000420 {cardinality="1"} ! number of partial least squares components
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000421 {cardinality="1"} ! type of validation
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/biomodels.kisao/10.1007/BFb0062108" xsd:anyURI {comment="Wold S, Martens H, Wold H (1983) The multivariate calibration method in chemistry solved by the PLS method. In: Lecture notes in Mathematics, Matrix Pencils. Heidelberg: Springer-Verlag. pp. 286-293."}
+property_value: skos:altLabel "PLSR" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "PLSR method" xsd:string {comment="EXACT"}
+property_value: skos:definition "Multivariate regression method based on estimated latent variables. Related to Principal Component Analysis (PCA) and Principal Component Regression (PCR)." xsd:string
 
 [Term]
-id: KISAO_0000417
+id: kisao:KISAO_0000417
 name: hierarchical cluster-based partial least squares regression method
 comment: Requested by Kristin Tøndel on Thursday, October 13, 2011 11:13:17 AM.
-is_a: KISAO_0000423 ! partial least squares regression-like method
-relationship: KISAO_0000360 KISAO_0000416 ! partial least squares regression method
-property_value: altLabel "HC-PLSR" xsd:string
-property_value: altLabel "Multivariate regression method based on separating the observations into clusters and generating Partial Least Squares Regression (PLSR) [http://identifiers.org/biomodels.kisao/KISAO_0000416] models within each cluster. This local regression analysis is suitable for very non-linear systems. PLSR is a regression method based on estimated latent variables, related to Principal Component Analysis (PCA) and Principal Component Regression (PCR).\nHierarchical cluster-based partial least squares regression method uses fuzzy C-means clustering, PLSR and Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA) or Naive Bayes for classification of new observations to be predicted." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000423 ! partial least squares regression-like method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000322 ! hybridity
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000420 ! number of partial least squares components
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000424 ! mean-centring of variables
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000425 ! standardising of variables
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000428 {cardinality="1"} ! matrix for clusterization
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000416 ! partial least squares regression method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1186/1752-0509-5-90" xsd:anyURI {comment="Tøndel K, Indahl UG, Gjuvsland AB, Vik JO, Hunter P, et al. (2011) Hierarchical Cluster-based Partial Least Squares Regression is an efficient tool for metamodelling of nonlinear dynamic models. BMC Systems Biology 5: 90."}
+property_value: skos:altLabel "HC-PLSR" xsd:string
+property_value: skos:altLabel "Multivariate regression method based on separating the observations into clusters and generating Partial Least Squares Regression (PLSR) [http://identifiers.org/biomodels.kisao/KISAO_0000416] models within each cluster. This local regression analysis is suitable for very non-linear systems. PLSR is a regression method based on estimated latent variables, related to Principal Component Analysis (PCA) and Principal Component Regression (PCR).\nHierarchical cluster-based partial least squares regression method uses fuzzy C-means clustering, PLSR and Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA) or Naive Bayes for classification of new observations to be predicted." xsd:string
 
 [Term]
-id: KISAO_0000418
+id: kisao:KISAO_0000418
 name: N-way partial least squares regression method
 comment: Requested by Kristin Tøndel on Thursday, October 13, 2011 11:33:06 AM.
-is_a: KISAO_0000423 ! partial least squares regression-like method
-property_value: altLabel "N-PLS" xsd:string {comment="EXACT"}
-property_value: altLabel "N-way partial least squares method" xsd:string {comment="EXACT"}
-property_value: altLabel "N-way PLSR" xsd:string {comment="EXACT"}
-property_value: definition "Multivariate regression method that can be used on N-way data. Based on Partial Least Squares Regression (PLSR) [http://identifiers.org/biomodels.kisao/KISAO_0000416], which is a regression method based on estimated latent variables. PLSR is related to Principal Component Analysis (PCA) and Principal Component Regression (PCR)." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000423 ! partial least squares regression-like method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000422 {cardinality="1"} ! number of N-way partial least squares regression factors
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1002/(SICI)1099-128X(199601)10:1<47::AID-CEM400>3.0.CO;2-C" xsd:anyURI {comment="Bro R (1996) Multiway calibration. Multilinear PLS. J. Chemometrics 10: 47-6."}
 property_value: seeAlso "http://www.models.life.ku.dk/nwaytoolbox" xsd:anyURI {comment="N-way toolbox website"}
+property_value: skos:altLabel "N-PLS" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "N-way partial least squares method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "N-way PLSR" xsd:string {comment="EXACT"}
+property_value: skos:definition "Multivariate regression method that can be used on N-way data. Based on Partial Least Squares Regression (PLSR) [http://identifiers.org/biomodels.kisao/KISAO_0000416], which is a regression method based on estimated latent variables. PLSR is related to Principal Component Analysis (PCA) and Principal Component Regression (PCR)." xsd:string
 
 [Term]
-id: KISAO_0000419
+id: kisao:KISAO_0000419
 name: metamodelling method
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: definition "Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://identifiers.org/doi/10.1186/1752-0509-5-90" xsd:anyURI {comment="Tøndel K, Indahl UG, Gjuvsland AB, Vik JO, Hunter P, et al. (2011) Hierarchical Cluster-based Partial Least Squares Regression is an efficient tool for metamodelling of nonlinear dynamic models. BMC Systems Biology 5: 90."}
+property_value: skos:definition "Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space." xsd:string
 
 [Term]
-id: KISAO_0000423
+id: kisao:KISAO_0000420
+name: number of partial least squares components
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000423 {all_only="true"} ! partial least squares regression-like method
+property_value: dc:creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/biomodels.kisao/10.1007/BFb0062108" xsd:anyURI {comment="Wold S, Martens H, Wold H (1983) The multivariate calibration method in chemistry solved by the PLS method. In: Lecture notes in Mathematics, Matrix Pencils. Heidelberg: Springer-Verlag. pp. 286-293."}
+property_value: skos:definition "Parameter used by 'partial least squares regression method' [http://identifiers.org/biomodels.kisao/KISAO_0000416] describing number of PLS components to include in the regression analysis." xsd:string
+
+[Term]
+id: kisao:KISAO_0000421
+name: type of validation
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000423 {all_only="true"} ! partial least squares regression-like method
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "Parameter of 'partial least squares regression method' [http://identifiers.org/biomodels.kisao/KISAO_0000416] describing how validation is performed. Possible values include cross-validation and test set validation." xsd:string
+
+[Term]
+id: kisao:KISAO_0000422
+name: number of N-way partial least squares regression factors
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000418 {all_only="true"} ! N-way partial least squares regression method
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:altLabel "number of factors" xsd:string {comment="EXACT"}
+property_value: skos:definition "Parameter of 'N-way partial least squares regression method' [http://identifiers.org/biomodels.kisao/KISAO_0000369] describing the number of factors to compute." xsd:string
+
+[Term]
+id: kisao:KISAO_0000423
 name: partial least squares regression-like method
-is_a: KISAO_0000419 ! metamodelling method
-property_value: definition "Method for building regression models between independent and dependent variables." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000419 ! metamodelling method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000421 {cardinality="1"} ! type of validation
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Method for building regression models between independent and dependent variables." xsd:string
+
+[Term]
+id: kisao:KISAO_0000424
+name: mean-centring of variables
+is_a: kisao:KISAO_0000430 ! variables preprocessing parameter
+disjoint_from: kisao:KISAO_0000425 ! standardising of variables
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000423 {all_only="true"} ! partial least squares regression-like method
+property_value: dc:creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1186/1752-0509-5-90" xsd:anyURI {comment="Tøndel K, Indahl UG, Gjuvsland AB, Vik JO, Hunter P, et al. (2011) Hierarchical Cluster-based Partial Least Squares Regression is an efficient tool for metamodelling of nonlinear dynamic models. BMC Systems Biology 5: 90."}
+property_value: skos:definition "A boolean parameter of the 'hierarchical cluster-based partial least squares regression method' [http://identifiers.org/biomodels.kisao/KISAO_0000417] specifying whether the variables were mean-centred prior to the regression analysis." xsd:string
+
+[Term]
+id: kisao:KISAO_0000425
+name: standardising of variables
+is_a: kisao:KISAO_0000430 ! variables preprocessing parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000423 {all_only="true"} ! partial least squares regression-like method
+property_value: dc:creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1186/1752-0509-5-90" xsd:anyURI {comment="Tøndel K, Indahl UG, Gjuvsland AB, Vik JO, Hunter P, et al. (2011) Hierarchical Cluster-based Partial Least Squares Regression is an efficient tool for metamodelling of nonlinear dynamic models. BMC Systems Biology 5: 90."}
+property_value: skos:definition "A boolean parameter of the 'hierarchical cluster-based partial least squares regression method' [http://identifiers.org/biomodels.kisao/KISAO_0000417] specifying whether the variables were standardised (divided by their standard deviations) prior to the regression analysis." xsd:string
+
+[Term]
+id: kisao:KISAO_0000427
+name: number of clusters
+is_a: kisao:KISAO_0000429 ! clusterization parameter
+disjoint_from: kisao:KISAO_0000428 ! matrix for clusterization
+property_value: dc:creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1186/1752-0509-5-90" xsd:anyURI {comment="Tøndel K, Indahl UG, Gjuvsland AB, Vik JO, Hunter P, et al. (2011) Hierarchical Cluster-based Partial Least Squares Regression is an efficient tool for metamodelling of nonlinear dynamic models. BMC Systems Biology 5: 90."}
+property_value: skos:definition "Parameter specifying the number of clusters used by C-means algorithm." xsd:string
+
+[Term]
+id: kisao:KISAO_0000428
+name: matrix for clusterization
+is_a: kisao:KISAO_0000429 ! clusterization parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000417 {all_only="true"} ! hierarchical cluster-based partial least squares regression method
+property_value: dc:creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1186/1752-0509-5-90" xsd:anyURI {comment="Tøndel K, Indahl UG, Gjuvsland AB, Vik JO, Hunter P, et al. (2011) Hierarchical Cluster-based Partial Least Squares Regression is an efficient tool for metamodelling of nonlinear dynamic models. BMC Systems Biology 5: 90."}
+property_value: skos:definition "A matrix to do the clustering in 'hierarchical cluster-based partial least squares regression method' [http://identifiers.org/biomodels.kisao/KISAO_0000417]." xsd:string
+
+[Term]
+id: kisao:KISAO_0000429
+name: clusterization parameter
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Parameter used by algorithms performing clusterization." xsd:string
+
+[Term]
+id: kisao:KISAO_0000430
+name: variables preprocessing parameter
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 
 [Term]
-id: KISAO_0000432
+id: kisao:KISAO_0000432
 name: IDA-like method
-is_a: KISAO_0000408 ! Newton-type method
-property_value: definition "Solves real differential-algebraic systems in N-space, in the general form F(t,y,y')=0,  y(t0)=y0,  y'(t0)=y'0. At each step, a Newton iteration [http://identifiers.org/biomodels.kisao/KISAO_0000408] leads to linear systems Jx=b, which are solved by one of five methods - two direct (dense or band; serial version only) and three Krylov [http://identifiers.org/biomodels.kisao/KISAO_0000354] (GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000353], BiCGStab [http://identifiers.org/biomodels.kisao/KISAO_0000392], or TFQMR [http://identifiers.org/biomodels.kisao/KISAO_0000396])." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000699 ! DAE Solver
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000467 {cardinality="1"} ! maximum step size
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://identifiers.org/doi/10.1145/1089014.1089020" xsd:anyURI {comment="Hindmarsh, A. C., et al., SUNDIALS: Suite of Nonlinear and Differential/Algebraic Equation Solvers, ACM Trans. Math. Softw., 31:363-396, 2005."}
+property_value: skos:definition "Solves real differential-algebraic systems in N-space, in the general form F(t,y,y')=0,  y(t0)=y0,  y'(t0)=y'0. At each step, a Newton iteration [http://identifiers.org/biomodels.kisao/KISAO_0000408] leads to linear systems Jx=b, which are solved by one of five methods - two direct (dense or band; serial version only) and three Krylov [http://identifiers.org/biomodels.kisao/KISAO_0000354] (GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000353], BiCGStab [http://identifiers.org/biomodels.kisao/KISAO_0000392], or TFQMR [http://identifiers.org/biomodels.kisao/KISAO_0000396])." xsd:string
 
 [Term]
-id: KISAO_0000433
+id: kisao:KISAO_0000433
 name: CVODE-like method
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: definition "Solves ODE initial value problems, in real N-space, written as y'=f(t,y),  y(t0)=y0. It is capable for stiff and non-stiff systems and uses two different linear multi-step methods, namely the Adam-Moulton [http://identifiers.org/biomodels.kisao/KISAO_0000280] method and the backward differentiation formula [http://identifiers.org/biomodels.kisao/KISAO_0000288]." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000694 ! ODE solver
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000467 {cardinality="1"} ! maximum step size
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000559 {maxCardinality="1"} ! initial step size
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://identifiers.org/doi/10.1145/1089014.1089020" xsd:anyURI {comment="Hindmarsh, A. C., et al., SUNDIALS: Suite of Nonlinear and Differential/Algebraic Equation Solvers, ACM Trans. Math. Softw., 31:363-396, 2005."}
+property_value: skos:definition "Solves ODE initial value problems, in real N-space, written as y'=f(t,y),  y(t0)=y0. It is capable for stiff and non-stiff systems and uses two different linear multi-step methods, namely the Adam-Moulton [http://identifiers.org/biomodels.kisao/KISAO_0000280] method and the backward differentiation formula [http://identifiers.org/biomodels.kisao/KISAO_0000288]." xsd:string
 
 [Term]
-id: KISAO_0000434
+id: kisao:KISAO_0000434
 name: Higham-Hall method
-is_a: KISAO_0000435 ! embedded Runge-Kutta 5(4) method
-property_value: altLabel "RK5(4)7FEql" xsd:string
-property_value: definition "The equilibrium theory of Hall and Higham (1988) can be used to determine whether a Runge-Kutta algorithm will perform smoothly when stability restricts the stepsize. Higham-Hall method is a fifth order embedded Runge-Kutta method [http://identifiers.org/biomodels.kisao/KISAO_0000302], which behaves smoothly with respect to the standard type of stepsize controllers." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000435 ! embedded Runge-Kutta 5(4) method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1016/0377-0427(90)90192-3" xsd:anyURI {comment="Higham, D.J. and Hall, G. (1990) Embedded Runge-Kutta formulae with stable equilibrium states. Journal of Computational and Applied Mathematics, 29 (1). pp. 25-33."}
+property_value: skos:altLabel "RK5(4)7FEql" xsd:string
+property_value: skos:definition "The equilibrium theory of Hall and Higham (1988) can be used to determine whether a Runge-Kutta algorithm will perform smoothly when stability restricts the stepsize. Higham-Hall method is a fifth order embedded Runge-Kutta method [http://identifiers.org/biomodels.kisao/KISAO_0000302], which behaves smoothly with respect to the standard type of stepsize controllers." xsd:string
 
 [Term]
-id: KISAO_0000435
+id: kisao:KISAO_0000435
 name: embedded Runge-Kutta 5(4) method
-is_a: KISAO_0000302 ! embedded Runge-Kutta method
-property_value: altLabel "RK5(4)" xsd:string
-property_value: definition "An embedded Runge-Kutta integrator of order 5(4)." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000302 ! embedded Runge-Kutta method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:altLabel "RK5(4)" xsd:string
+property_value: skos:definition "An embedded Runge-Kutta integrator of order 5(4)." xsd:string
 
 [Term]
-id: KISAO_0000436
+id: kisao:KISAO_0000436
 name: Dormand-Prince 8(5,3) method
-is_a: KISAO_0000302 ! embedded Runge-Kutta method
-property_value: definition "This method is based on an 8(6) method by Dormand and Prince (i.e. order 8 for the integration and order 6 for error estimation) modified by Hairer and Wanner to use a 5th order error estimator with 3rd order correction." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000302 ! embedded Runge-Kutta method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000538 {maxCardinality="1"} ! safety factor on new step selection
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000539 {maxCardinality="1"} ! minimum factor to change step size by
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000540 {maxCardinality="1"} ! maximum factor to change step size by
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000541 {maxCardinality="1"} ! beta parameter for stabilized step size control
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000559 {maxCardinality="1"} ! initial step size
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+property_value: skos:definition "This method is based on an 8(6) method by Dormand and Prince (i.e. order 8 for the integration and order 6 for error estimation) modified by Hairer and Wanner to use a 5th order error estimator with 3rd order correction." xsd:string
 
 [Term]
-id: KISAO_0000437
+id: kisao:KISAO_0000437
 name: flux balance analysis
 comment: Requested by Frank T. Bergmann on Thursday, November 29, 2012 9:51:58 AM.
-is_a: KISAO_0000407 ! steady state method
-is_a: KISAO_0000622 ! flux balance method
-disjoint_from: KISAO_0000526 ! flux variability analysis
-property_value: altLabel "FBA" xsd:string
-property_value: definition "Flux balance analysis is a mathematical approach for analyzing the flow of metabolites through a metabolic network." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000622 ! flux balance method
+is_a: kisao:KISAO_0000630 ! general steady state method
+disjoint_from: kisao:KISAO_0000526 ! flux variability analysis
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1038/nbt.1614" xsd:anyURI {comment="Jeffrey D Orth, Ines Thiele and Bernhard O Palsson (2010) What is flux balance analysis? Nature Biotechnology 28, 245–248"}
+property_value: skos:altLabel "FBA" xsd:string
+property_value: skos:definition "Flux balance analysis is a mathematical approach for analyzing the flow of metabolites through a metabolic network." xsd:string
 
 [Term]
-id: KISAO_0000447
+id: kisao:KISAO_0000447
 name: COAST
 comment: Requested by Mark Moeller on Friday, January 25, 2013 11:11:30 AM.
-is_a: KISAO_0000352 ! hybrid method
-property_value: altLabel "controllable approximative stochastic reaction algorithm" xsd:string
-property_value: definition "An approximative algorithm for stochastic simulations of chemical reaction systems based on three different modeling levels: for small numbers of particles an exact [http://identifiers.org/biomodels.kisao/KISAO_0000236] stochastic [http://identifiers.org/biomodels.kisao/KISAO_0000104] model; for intermediate numbers an approximative [http://identifiers.org/biomodels.kisao/KISAO_0000237], but computationally more efficient stochastic [http://identifiers.org/biomodels.kisao/KISAO_0000104] model based on discrete Gaussian distributions; and for large numbers the deterministic [http://identifiers.org/biomodels.kisao/KISAO_0000103] reaction kinetics. In every simulation time step, the subdivision of the reaction channels into the three different modeling levels is done automatically, where all approximations applied can be controlled by a single error parameter for which an appropriate value can easily be found." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000352 ! hybrid method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000211 {cardinality="1"} ! absolute tolerance
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/pubmed/17100426" xsd:anyURI {comment="Holger Wagner, Mark Moeller, and Klaus Prank (2006) COAST: Controllable approximative stochastic reaction algorithm. J. Chem. Phys. 125, 174104"}
+property_value: skos:altLabel "controllable approximative stochastic reaction algorithm" xsd:string
+property_value: skos:definition "An approximative algorithm for stochastic simulations of chemical reaction systems based on three different modeling levels: for small numbers of particles an exact [http://identifiers.org/biomodels.kisao/KISAO_0000236] stochastic [http://identifiers.org/biomodels.kisao/KISAO_0000104] model; for intermediate numbers an approximative [http://identifiers.org/biomodels.kisao/KISAO_0000237], but computationally more efficient stochastic [http://identifiers.org/biomodels.kisao/KISAO_0000104] model based on discrete Gaussian distributions; and for large numbers the deterministic [http://identifiers.org/biomodels.kisao/KISAO_0000103] reaction kinetics. In every simulation time step, the subdivision of the reaction channels into the three different modeling levels is done automatically, where all approximations applied can be controlled by a single error parameter for which an appropriate value can easily be found." xsd:string
 
 [Term]
-id: KISAO_0000448
+id: kisao:KISAO_0000448
 name: logical model simulation method
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: definition "Qualitative (logical) models specify the evolution rules of their components. In each state a number of transitions are enabled. A 'logical model simulation method' guides the choice of the transitions processed at each step." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000105 ! discrete variable
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://www.identifiers.org/pubmed/22141422" xsd:anyURI {comment="Daniel Machado et al. Modeling formalisms in Systems Biology. AMB Express 2011, 1:45"}
+property_value: skos:definition "Qualitative (logical) models specify the evolution rules of their components. In each state a number of transitions are enabled. A 'logical model simulation method' guides the choice of the transitions processed at each step." xsd:string
 
 [Term]
-id: KISAO_0000449
+id: kisao:KISAO_0000449
 name: synchronous logical model simulation method
-is_a: KISAO_0000448 ! logical model simulation method
-disjoint_from: KISAO_0000450 ! asynchronous logical model simulation method
-property_value: definition "Qualitative (logical) models specify the evolution rules of their components. In the case of a synchronous updating all enabled transitions are processed simultaneously. " xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000448 ! logical model simulation method
+disjoint_from: kisao:KISAO_0000450 ! asynchronous logical model simulation method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000493 ! synchronous updating policy
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "Qualitative (logical) models specify the evolution rules of their components. In the case of a synchronous updating all enabled transitions are processed simultaneously. " xsd:string
 
 [Term]
-id: KISAO_0000450
+id: kisao:KISAO_0000450
 name: asynchronous logical model simulation method
-is_a: KISAO_0000448 ! logical model simulation method
-property_value: definition "Qualitative (logical) models specify the evolution rules of their components. It the case of an asynchronous updating all enabled transitions are performed independently: a state has as many successors as the number of transitions enabled in this state. An 'asynchronous logical model simulation method' specifies a rule to guide the choice of a unique transition at each step (for example random)." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000448 ! logical model simulation method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000104 ! stochastic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000492 ! asynchronous updating policy
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000574 ! species transition probabilities
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "Qualitative (logical) models specify the evolution rules of their components. It the case of an asynchronous updating all enabled transitions are performed independently: a state has as many successors as the number of transitions enabled in this state. An 'asynchronous logical model simulation method' specifies a rule to guide the choice of a unique transition at each step (for example random)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000451
+name: type of updating policy
+is_a: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A rule to guide the choice of a unique transition at each step used by an 'asynchronous logical model simulation method' [http://identifiers.org/biomodels.kisao/KISAO_0000450]." xsd:string
+
+[Term]
+id: kisao:KISAO_0000452
+name: random updating policy
+is_a: kisao:KISAO_0000451 ! type of updating policy
+disjoint_from: kisao:KISAO_0000453 ! ordered updating policy
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "An updating policy that chooses a transition randomly." xsd:string
+
+[Term]
+id: kisao:KISAO_0000453
+name: ordered updating policy
+is_a: kisao:KISAO_0000451 ! type of updating policy
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "An updating policy that chooses a transition in a definite way." xsd:string
+
+[Term]
+id: kisao:KISAO_0000454
+name: constant updating policy
+is_a: kisao:KISAO_0000453 ! ordered updating policy
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "An updating policy that chooses a transition in a constant way." xsd:string
+
+[Term]
+id: kisao:KISAO_0000455
+name: prioritized updating policy
+is_a: kisao:KISAO_0000453 ! ordered updating policy
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "An updating policy that chooses a transition in a prioritized way." xsd:string
 
 [Term]
-id: KISAO_0000468
+id: kisao:KISAO_0000467
+name: maximum step size
+comment: Requested by Andrew Miller on Tuesday, June 4, 2013 2:33:51 AM.
+is_a: kisao:KISAO_0000242 ! error control parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "An upper limit, in the units of the bound variable over which a numerical integration is being performed, that an adaptive step size numerical integration algorithm should take." xsd:string
+
+[Term]
+id: kisao:KISAO_0000468
 name: maximal timestep method
-comment: Requested by Andrzej Kierzek on Thursday, April 24, 2014 12:40:35 PM
-comment: Used to simulate systems involving reactions with propensities varying by many orders of magnitude.
-is_a: KISAO_0000352 ! hybrid method
-relationship: KISAO_0000360 KISAO_0000027 ! Gibson-Bruck next reaction algorithm
-relationship: KISAO_0000360 KISAO_0000039 ! tau-leaping method
-property_value: definition "Hybrid simulation algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000352] combining Gibson and Bruck algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000027] with the Gillespie tau-leap method [http://www.biomodels.net/kisao/KISAO#KISAO_0000039]." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+comment: Requested by Andrzej Kierzek on Thursday, April 24, 2014 12:40:35 PM\n\nUsed to simulate systems involving reactions with propensities varying by many orders of magnitude.
+is_a: kisao:KISAO_0000352 ! hybrid method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000104 ! stochastic system behaviour
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000469 ! maximal timestep
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000027 ! Gibson-Bruck next reaction algorithm
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000039 ! tau-leaping method
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/pubmed/14990466" xsd:anyURI {comment="Puchalka J, Kierzek AM. Bridging the gap between stochastic and deterministic regimes in the kinetic simulations of the biochemical reaction networks. Biophys J. 2004 Mar;86(3):1357-72.\n"}
+property_value: skos:definition "Hybrid simulation algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000352] combining Gibson and Bruck algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000027] with the Gillespie tau-leap method [http://www.biomodels.net/kisao/KISAO#KISAO_0000039]." xsd:string
+
+[Term]
+id: kisao:KISAO_0000469
+name: maximal timestep
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/14990466" xsd:anyURI {comment="Puchalka J, Kierzek AM. Bridging the gap between stochastic and deterministic regimes in the kinetic simulations of the biochemical reaction networks. Biophys J. 2004 Mar;86(3):1357-72."}
+property_value: skos:definition "Key parameter of the 'maximal timestep method' [http://www.biomodels.net/kisao/KISAO#KISAO_0000468]. If Gillespie [http://www.biomodels.net/kisao/KISAO#KISAO_0000027] waiting time is longer than maximal timestep, slow reaction is not fired and tau-leap [http://www.biomodels.net/kisao/KISAO#KISAO_0000039] step is executed for fast reactions. Otherwise, slow reaction is fired and tau-leap [http://www.biomodels.net/kisao/KISAO#KISAO_0000039] is executed with shorter time step." xsd:string
 
 [Term]
-id: KISAO_0000470
+id: kisao:KISAO_0000470
 name: optimization algorithm
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: altLabel "optimization method" xsd:string
-property_value: definition "An optimization algorithm tries to find the minumum or maximum of an arbitrary function. It takes a function of one or several variables and determines the values for the variables so that the function value is optimal." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000689 ! mathematical system
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://en.wikipedia.org/wiki/Mathematical_optimization#Optimization_algorithms" xsd:anyURI
 property_value: seeAlso "http://identifiers.org/isbn/0691102872" xsd:anyURI {comment="Brinkhuis J, Tikhomirov V. Optimization: Insights and Applications\nPrinceton Series in Applied Mathematics (illustrated), Princeton University Press, 2005."}
+property_value: skos:altLabel "optimization method" xsd:string
+property_value: skos:definition "An optimization algorithm tries to find the minumum or maximum of an arbitrary function. It takes a function of one or several variables and determines the values for the variables so that the function value is optimal." xsd:string
 
 [Term]
-id: KISAO_0000471
+id: kisao:KISAO_0000471
 name: local optimization algorithm
-is_a: KISAO_0000470 ! optimization algorithm
-disjoint_from: KISAO_0000472 ! global optimization algorithm
-property_value: altLabel "local optimiation method" xsd:string
-property_value: definition "A local optimization algorithm is an optimisation algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000470] that only finds a local optimum of a function. If several optima exist for the function, it usually depends on the starting values for the variables which optimum is found." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000470 ! optimization algorithm
+disjoint_from: kisao:KISAO_0000472 ! global optimization algorithm
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:altLabel "local optimiation method" xsd:string
+property_value: skos:definition "A local optimization algorithm is an optimisation algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000470] that only finds a local optimum of a function. If several optima exist for the function, it usually depends on the starting values for the variables which optimum is found." xsd:string
 
 [Term]
-id: KISAO_0000472
+id: kisao:KISAO_0000472
 name: global optimization algorithm
-is_a: KISAO_0000470 ! optimization algorithm
-property_value: altLabel "global optimization method" xsd:string
-property_value: definition "A global optimization algorithm is an optimization algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000470] that tries to find the global optimum of a function. If a function has several minima/maxima with in the allowed range of variable values, the global minimum/maximum is the one with the smallest/largest function value." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000470 ! optimization algorithm
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000488 ! seed
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:altLabel "global optimization method" xsd:string
+property_value: skos:definition "A global optimization algorithm is an optimization algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000470] that tries to find the global optimum of a function. If a function has several minima/maxima with in the allowed range of variable values, the global minimum/maximum is the one with the smallest/largest function value." xsd:string
 
 [Term]
-id: KISAO_0000473
+id: kisao:KISAO_0000473
 name: Bayesian inference algorithm
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: definition "A bayesian inference algorithm calculates a posterior probability distribution from a prior probability distribution and some additional evidence in the form of a likelyhood function." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://en.wikipedia.org/wiki/Bayesian_inference" xsd:anyURI
 property_value: seeAlso "http://identifiers.org/isbn/111803144X" xsd:anyURI {comment="George E. P. Box, George C. Tiao. Bayesian Inference in Statistical Analysis, Volume 40 of Wiley Classics Library. John Wiley & Sons (reprint, revised), 2011."}
-
-[Term]
-id: KISAO_0000491
+property_value: skos:definition "A bayesian inference algorithm calculates a posterior probability distribution from a prior probability distribution and some additional evidence in the form of a likelyhood function." xsd:string
+
+[Term]
+id: kisao:KISAO_0000475
+name: integration method
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/opencor" xsd:anyURI {comment="OpenCOR"}
+property_value: seeAlso "http://identifiers.org/doi/10.3389/fphys.2015.00026" xsd:anyURI {comment="Garny A and Hunter PJ (2015) OpenCOR: a modular and interoperable approach to computational biology. Front. Physiol. 6:26"}
+property_value: skos:definition "the integration method used by the solver" xsd:string
+
+[Term]
+id: kisao:KISAO_0000476
+name: iteration type
+comment: Requested in https://sourceforge.net/p/kisao/feature-requests/12/
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/opencor" xsd:anyURI {comment="OpenCOR"}
+property_value: seeAlso "http://identifiers.org/doi/10.3389/fphys.2015.00026" xsd:anyURI {comment="Garny A and Hunter PJ (2015) OpenCOR: a modular and interoperable approach to computational biology. Front. Physiol. 6:26"}
+property_value: skos:definition "the type of iteration used by the solver" xsd:string
+
+[Term]
+id: kisao:KISAO_0000477
+name: linear solver
+comment: Requested in https://sourceforge.net/p/kisao/feature-requests/12/
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/opencor" xsd:anyURI {comment="OpenCOR"}
+property_value: seeAlso "http://identifiers.org/doi/10.3389/fphys.2015.00026" xsd:anyURI {comment="Garny A and Hunter PJ (2015) OpenCOR: a modular and interoperable approach to computational biology. Front. Physiol. 6:26"}
+property_value: skos:definition "the linear solver used by the solver during a Newton iteration" xsd:string
+
+[Term]
+id: kisao:KISAO_0000478
+name: preconditioner
+comment: Requested in https://sourceforge.net/p/kisao/feature-requests/12/
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/opencor" xsd:anyURI {comment="OpenCOR"}
+property_value: seeAlso "http://identifiers.org/doi/10.3389/fphys.2015.00026" xsd:anyURI {comment="Garny A and Hunter PJ (2015) OpenCOR: a modular and interoperable approach to computational biology. Front. Physiol. 6:26"}
+property_value: skos:definition "the preconditioner, if any, used by the solver when using a GMRES, BiCGStab or TFQMR linear solver during a Newton iteration." xsd:string
+
+[Term]
+id: kisao:KISAO_0000479
+name: upper half-bandwidth
+comment: Requested in https://sourceforge.net/p/kisao/feature-requests/12/
+is_a: kisao:KISAO_0000482 ! half-bandwith parameter
+disjoint_from: kisao:KISAO_0000480 ! lower half-bandwidth
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/opencor" xsd:anyURI {comment="OpenCOR"}
+property_value: seeAlso "http://identifiers.org/doi/10.3389/fphys.2015.00026" xsd:anyURI {comment="Garny A and Hunter PJ (2015) OpenCOR: a modular and interoperable approach to computational biology. Front. Physiol. 6:26"}
+property_value: skos:definition "the upper half-bandwidth value used by the Banded linear solver or preconditioner (a value between 0 and n-1 with n the number of ODEs/DAEs in the model)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000480
+name: lower half-bandwidth
+comment: Requested in https://sourceforge.net/p/kisao/feature-requests/12/
+is_a: kisao:KISAO_0000482 ! half-bandwith parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/opencor" xsd:anyURI {comment="OpenCOR"}
+property_value: seeAlso "http://identifiers.org/doi/10.3389/fphys.2015.00026" xsd:anyURI {comment="Garny A and Hunter PJ (2015) OpenCOR: a modular and interoperable approach to computational biology. Front. Physiol. 6:26"}
+property_value: skos:definition "the lower half-bandwidth value used by the Banded linear solver or preconditioner (a value between 0 and n-1 with n the number of ODEs/DAEs in the model)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000481
+name: interpolate solution
+comment: Requested in https://sourceforge.net/p/kisao/feature-requests/12/
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/opencor" xsd:anyURI {comment="OpenCOR"}
+property_value: seeAlso "http://identifiers.org/doi/10.3389/fphys.2015.00026" xsd:anyURI {comment="Garny A and Hunter PJ (2015) OpenCOR: a modular and interoperable approach to computational biology. Front. Physiol. 6:26"}
+property_value: skos:definition "whether the solver returns an interpolated solution." xsd:string
+
+[Term]
+id: kisao:KISAO_0000482
+name: half-bandwith parameter
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: skos:definition "the parameter related to the half-bandwidth value used by the Banded linear solver or preconditioner." xsd:string
+
+[Term]
+id: kisao:KISAO_0000483
+name: step size
+comment: Requested in https://sourceforge.net/p/kisao/feature-requests/13/
+is_a: kisao:KISAO_0000242 ! error control parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "the size of every step of the algorithm" xsd:string
+
+[Term]
+id: kisao:KISAO_0000484
+name: maximum order
+is_a: kisao:KISAO_0000594 ! order
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "Roadrunner" xsd:string
+property_value: skos:definition "Maximum order of method. For example, in Roadrunner it can be used for two parameters that one can set for deterministic runs: 'maximum_bdf_order' and 'maximum_adams_order'." xsd:string
+
+[Term]
+id: kisao:KISAO_0000485
+name: minimum step size
+is_a: kisao:KISAO_0000242 ! error control parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "A lower limit, in the units of the bound variable over which a numerical integration is being performed, that a numerical integration algorithm with variable step size should take." xsd:string
+
+[Term]
+id: kisao:KISAO_0000486
+name: maximum iterations
+is_a: kisao:KISAO_0000244 ! granularity control parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:altLabel "iteration limit" xsd:string
+property_value: skos:definition "For algorithms that iterate to a solution (steady state finders in particular), a limit on the number of iterations that should be performed." xsd:string
+
+[Term]
+id: kisao:KISAO_0000487
+name: minimum damping
+comment: The damping factor is a variable for at least some steady state algorithms: roadrunner allows you to set the minimum value for this.
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: kisao:isImplementedIn "Roadrunner" xsd:string
+
+[Term]
+id: kisao:KISAO_0000488
+name: seed
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: skos:altLabel "random seed" xsd:string
+property_value: skos:definition "Random seed of a stochastic algorithm. Setting it allows one to reproduce their results while running the same algorithm on the same computer." xsd:string
+
+[Term]
+id: kisao:KISAO_0000491
 name: discrete event simulation algorithm
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: altLabel "DES" xsd:string
-property_value: definition "Discrete Event Simulation algorithm refers to the simulation of systems whose (countable) discrete states change over time and are event-driven." xsd:string
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000105 ! discrete variable
 property_value: seeAlso "http://identifiers.org/isbn/0387333320" xsd:anyURI {comment="C.G. Cassandras & S. Lafortune \"Introduction to Discrete Event Systems\", Chapt 1 2nd Ed 2008. Springer"}
+property_value: skos:altLabel "DES" xsd:string
+property_value: skos:definition "Discrete Event Simulation algorithm refers to the simulation of systems whose (countable) discrete states change over time and are event-driven." xsd:string
+
+[Term]
+id: kisao:KISAO_0000492
+name: asynchronous updating policy
+is_a: kisao:KISAO_0000451 ! type of updating policy
+disjoint_from: kisao:KISAO_0000493 ! synchronous updating policy
+property_value: skos:definition "An updating policy where all enabled transitions (events) occur independently. Thus a state has as many successors as the number of transitions enabled in this state." xsd:string
+
+[Term]
+id: kisao:KISAO_0000493
+name: synchronous updating policy
+is_a: kisao:KISAO_0000451 ! type of updating policy
+property_value: skos:definition "An updating policy where all enabled transitions occur simultaneously. Thus a state will have at most one successor." xsd:string
+
+[Term]
+id: kisao:KISAO_0000494
+name: fully asynchronous updating policy
+is_a: kisao:KISAO_0000492 ! asynchronous updating policy
+property_value: skos:definition "An updating policy where all enabled transitions occur either independently or (partially) simultaneously. (i.e. considering all possible combinations of enabled transitions). Thus a state has as many successors as the number of combinations of transitions enabled in this state." xsd:string
 
 [Term]
-id: KISAO_0000496
+id: kisao:KISAO_0000495
+name: random asynchronous updating policy
+is_a: kisao:KISAO_0000452 ! random updating policy
+is_a: kisao:KISAO_0000492 ! asynchronous updating policy
+property_value: skos:definition "An updating policy where a single transition is picked randomly from the set of transitions enabled in this state. Thus a state will have at most one successor." xsd:string
+
+[Term]
+id: kisao:KISAO_0000496
 name: CVODES
 comment: CVODES is a superset of CVODE [http://identifiers.org/biomodels.kisao/KISAO_0000019] and hence all options available to CVODE (with the exception of the FCVODE interface module) are also available for CVODES. Both integration methods (Adams-Moulton [http://identifiers.org/biomodels.kisao/KISAO_0000280] and BDF [http://identifiers.org/biomodels.kisao/KISAO_0000288]) and the corresponding nonlinear iteration methods, as well as all linear solver and preconditioner modules, are available for the integration of the original ODEs, the sensitivity systems, or the adjoint system.
-is_a: KISAO_0000433 ! CVODE-like method
-relationship: KISAO_0000359 KISAO_0000019 ! CVODE
-relationship: KISAO_0000360 KISAO_0000497 ! KLU
-property_value: definition "CVODES is a solver for stiff and nonstiff ODE systems (initial value problem) given in explicit form y’ = f(t,y,p) with sensitivity analysis capabilities (both forward and adjoint modes)." xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/amici" xsd:anyURI {comment="AMICI"}
-property_value: isImplementedIn "SUNDIALS" xsd:string
+is_a: kisao:KISAO_0000433 ! CVODE-like method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000543 {maxCardinality="1"} ! stability limit detection flag
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000555 {maxCardinality="1"} ! absolute quadrature tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000556 {maxCardinality="1"} ! relative quadrature tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000557 {maxCardinality="1"} ! absolute steady-state tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000558 {maxCardinality="1"} ! relative steady-state tolerance
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000019 ! CVODE
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000497 ! KLU
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/amici" xsd:anyURI {comment="AMICI"}
+property_value: kisao:isImplementedIn "SUNDIALS" xsd:string
 property_value: seeAlso "http://computation.llnl.gov/projects/sundials/cvodes" xsd:anyURI
+property_value: skos:definition "CVODES is a solver for stiff and nonstiff ODE systems (initial value problem) given in explicit form y’ = f(t,y,p) with sensitivity analysis capabilities (both forward and adjoint modes)." xsd:string
 
 [Term]
-id: KISAO_0000497
+id: kisao:KISAO_0000497
 name: KLU
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: altLabel "\"Clark Kent\" LU factorization algorithm" xsd:string
-property_value: definition "KLU is a software package and an algorithm for solving sparse unsymmetric linear systems of equations that arise in circuit simulation applications. It relies on a permutation to Block Triangular Form (BTF), several methods for finding a fill-reducing ordering (variants of approximate minimum degree and nested dissection), and Gilbert/Peierls’ sparse left-looking LU factorization algorithm to factorize each block. The package is written in C and includes a MATLAB interface." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1145/1824801.1824814" xsd:anyURI {comment="Davis, Timothy A., and Ekanathan Palamadai Natarajan. \"Algorithm 907: KLU, a direct sparse solver for circuit simulation problems.\" ACM Transactions on Mathematical Software (TOMS) 37.3 (2010): 36."}
+property_value: skos:altLabel "\"Clark Kent\" LU factorization algorithm" xsd:string
+property_value: skos:definition "KLU is a software package and an algorithm for solving sparse unsymmetric linear systems of equations that arise in circuit simulation applications. It relies on a permutation to Block Triangular Form (BTF), several methods for finding a fill-reducing ordering (variants of approximate minimum degree and nested dissection), and Gilbert/Peierls’ sparse left-looking LU factorization algorithm to factorize each block. The package is written in C and includes a MATLAB interface." xsd:string
+
+[Term]
+id: kisao:KISAO_0000498
+name: number of runs
+comment: Requested in https://sourceforge.net/p/kisao/feature-requests/31/
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "The number of runs that a simulation should perform. Typically used to specify the number of runs for a stochastic simulation." xsd:string
 
 [Term]
-id: KISAO_0000499
+id: kisao:KISAO_0000499
 name: dynamic flux balance analysis
 comment: Ticket 32
-is_a: KISAO_0000352 ! hybrid method
-is_a: KISAO_0000622 ! flux balance method
-relationship: KISAO_0000246 KISAO_0000437 ! flux balance analysis
-property_value: altLabel "DFBA" xsd:string
-property_value: definition "Dynamic flux balance analysis (DFBA) enables the simulation of dynamic biological systems by assuming organisms reach steady state rapidly in response to changes in the extracellular environment. DFBA couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000352 ! hybrid method
+is_a: kisao:KISAO_0000622 ! flux balance method
+relationship: kisao:KISAO_0000246 kisao:KISAO_0000437 ! flux balance analysis
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 property_value: seeAlso "http://identifiers.org/doi/10.1186/s12859-014-0409-8" xsd:anyURI {comment="DFBAlab: a fast and reliable MATLAB code for dynamic flux balance analysis.\nGomez JA, Höffner K, Barton PI. BMC Bioinformatics. 2014 Dec 18;15:409."}
+property_value: skos:altLabel "DFBA" xsd:string
+property_value: skos:definition "Dynamic flux balance analysis (DFBA) enables the simulation of dynamic biological systems by assuming organisms reach steady state rapidly in response to changes in the extracellular environment. DFBA couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches." xsd:string
 
 [Term]
-id: KISAO_0000500
+id: kisao:KISAO_0000500
 name: SOA-DFBA
 comment: Ticket 32
-is_a: KISAO_0000499 ! dynamic flux balance analysis
-disjoint_from: KISAO_0000501 ! DOA-DFBA
-relationship: KISAO_0000360 KISAO_0000030 ! Euler forward method
-property_value: altLabel "SOA" xsd:string
-property_value: altLabel "static optimization approach dynamic flux balance analysis" xsd:string
-property_value: definition "Dynamic Flux Balance Analysis (DFBA) [http://identifiers.org/biomodels.kisao/KISAO_0000499] couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches. The static optimization approach (SOA) uses the Euler forward method [http://identifiers.org/biomodels.kisao/KISAO_0000030], solving the embedded LPs at each time step. The FBA fluxes are assumed to be constant during the time step." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "DFBAlab" xsd:string
+is_a: kisao:KISAO_0000499 ! dynamic flux balance analysis
+disjoint_from: kisao:KISAO_0000501 ! DOA-DFBA
+relationship: kisao:KISAO_0000360 kisao:KISAO_0000030 ! Euler forward method
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "DFBAlab" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1186/s12859-014-0409-8" xsd:anyURI {comment="DFBAlab: a fast and reliable MATLAB code for dynamic flux balance analysis.\nGomez JA, Höffner K, Barton PI. BMC Bioinformatics. 2014 Dec 18;15:409."}
+property_value: skos:altLabel "SOA" xsd:string
+property_value: skos:altLabel "static optimization approach dynamic flux balance analysis" xsd:string
+property_value: skos:definition "Dynamic Flux Balance Analysis (DFBA) [http://identifiers.org/biomodels.kisao/KISAO_0000499] couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches. The static optimization approach (SOA) uses the Euler forward method [http://identifiers.org/biomodels.kisao/KISAO_0000030], solving the embedded LPs at each time step. The FBA fluxes are assumed to be constant during the time step." xsd:string
 
 [Term]
-id: KISAO_0000501
+id: kisao:KISAO_0000501
 name: DOA-DFBA
 comment: Ticket 32
-is_a: KISAO_0000499 ! dynamic flux balance analysis
-property_value: altLabel "DOA" xsd:string
-property_value: altLabel "dynamic optimization approach dynamic flux balance analysis" xsd:string
-property_value: definition "Dynamic Flux Balance Analysis (DFBA) [http://identifiers.org/biomodels.kisao/KISAO_0000499] couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches. The dynamic optimization approach (DOA) discretizes the time horizon and optimizes simultaneously over the entire time period of interest by solving a nonlinear programming problem (NLP)." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "DFBAlab" xsd:string
+is_a: kisao:KISAO_0000499 ! dynamic flux balance analysis
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "DFBAlab" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1186/s12859-014-0409-8" xsd:anyURI {comment="DFBAlab: a fast and reliable MATLAB code for dynamic flux balance analysis.\nGomez JA, Höffner K, Barton PI. BMC Bioinformatics. 2014 Dec 18;15:409."}
+property_value: skos:altLabel "DOA" xsd:string
+property_value: skos:altLabel "dynamic optimization approach dynamic flux balance analysis" xsd:string
+property_value: skos:definition "Dynamic Flux Balance Analysis (DFBA) [http://identifiers.org/biomodels.kisao/KISAO_0000499] couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches. The dynamic optimization approach (DOA) discretizes the time horizon and optimizes simultaneously over the entire time period of interest by solving a nonlinear programming problem (NLP)." xsd:string
 
 [Term]
-id: KISAO_0000502
+id: kisao:KISAO_0000502
 name: DA-DFBA
 comment: Ticket 32
-is_a: KISAO_0000499 ! dynamic flux balance analysis
-property_value: altLabel "DA" xsd:string
-property_value: altLabel "direct approach dynamics flux balance analysis" xsd:string
-property_value: definition "Dynamic Flux Balance Analysis (DFBA) [http://identifiers.org/biomodels.kisao/KISAO_0000499] couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches. The direct approach (DA) includes the LP solver in the right-hand side evaluator for the ordinary differential equations (ODEs) and takes advantage of reliable implicit ODE integrators with adaptive step size for error control." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "DFBAlab" xsd:string
+is_a: kisao:KISAO_0000499 ! dynamic flux balance analysis
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "DFBAlab" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1186/s12859-014-0409-8" xsd:anyURI {comment="DFBAlab: a fast and reliable MATLAB code for dynamic flux balance analysis.\nGomez JA, Höffner K, Barton PI. BMC Bioinformatics. 2014 Dec 18;15:409."}
+property_value: skos:altLabel "DA" xsd:string
+property_value: skos:altLabel "direct approach dynamics flux balance analysis" xsd:string
+property_value: skos:definition "Dynamic Flux Balance Analysis (DFBA) [http://identifiers.org/biomodels.kisao/KISAO_0000499] couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches. The direct approach (DA) includes the LP solver in the right-hand side evaluator for the ordinary differential equations (ODEs) and takes advantage of reliable implicit ODE integrators with adaptive step size for error control." xsd:string
 
 [Term]
-id: KISAO_0000503
+id: kisao:KISAO_0000503
 name: simulated annealing
-is_a: KISAO_0000472 ! global optimization algorithm
-disjoint_from: KISAO_0000504 ! random search
-property_value: definition "Simulated annealing is an optimization algorithm first proposed by Kirkpatrick et al. and was inspired by statistical mechanics and the way in which perfect crystals are formed. Perfect crystals are formed by first melting the substance of interest, and then cooling it very slowly. At large temperatures the particles vibrate with wide amplitude and this allows a search for global optimum. As the temperature decreases so do the vibrations until the system settles to the global optimum (the perfect crystal).\n\nThe simulated annealing optimization algorithm uses a similar concept: the objective function is considered a measure of the energy of the system and this is maintained constant for a certain number of iterations (a temperature cycle). In each iteration, the parameters are changed to a nearby location in parameter space and the new objective function value calculated; if it decreased, then the new state is accepted, if it increased then the new state is accepted with a probability that follows a Boltzmann distribution (higher temperature means higher probability of accepting the new state). After a fixed number of iterations, the stopping criterion is checked; if it is not time to stop, then the system's temperature is reduced and the algorithm continues.\n\nSimulated annealing is a stochastic algorithm that is guaranteed to converge if ran for an infinite number of iterations. It is one of the most robust global optimization algorithms, although it is also one of the slowest. (Be warned that simulated annealing can run for hours or even days!)." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000472 ! global optimization algorithm
+disjoint_from: kisao:KISAO_0000504 ! random search
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000211 ! absolute tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000522 ! start temperature
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000523 ! cooling factor
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/doi/10.1126/science.220.4598.671" xsd:anyURI {comment="S. Kirkpatrick, J., C.D. Gelatt, and M. P. Vecchi. Optimization by simulated annealing. Science. 220. 671 - 680. 1983."}
+property_value: skos:definition "Simulated annealing is an optimization algorithm first proposed by Kirkpatrick et al. and was inspired by statistical mechanics and the way in which perfect crystals are formed. Perfect crystals are formed by first melting the substance of interest, and then cooling it very slowly. At large temperatures the particles vibrate with wide amplitude and this allows a search for global optimum. As the temperature decreases so do the vibrations until the system settles to the global optimum (the perfect crystal).\n\nThe simulated annealing optimization algorithm uses a similar concept: the objective function is considered a measure of the energy of the system and this is maintained constant for a certain number of iterations (a temperature cycle). In each iteration, the parameters are changed to a nearby location in parameter space and the new objective function value calculated; if it decreased, then the new state is accepted, if it increased then the new state is accepted with a probability that follows a Boltzmann distribution (higher temperature means higher probability of accepting the new state). After a fixed number of iterations, the stopping criterion is checked; if it is not time to stop, then the system's temperature is reduced and the algorithm continues.\n\nSimulated annealing is a stochastic algorithm that is guaranteed to converge if ran for an infinite number of iterations. It is one of the most robust global optimization algorithms, although it is also one of the slowest. (Be warned that simulated annealing can run for hours or even days!)." xsd:string
 
 [Term]
-id: KISAO_0000504
+id: kisao:KISAO_0000504
 name: random search
-is_a: KISAO_0000472 ! global optimization algorithm
-property_value: definition "Random search is an optimization method that attempts to find the optimum by testing the objective function's value on a series of combinations of random values of the adjustable parameters. The random values are generated complying with any boundaries selected by the user, furthermore, any combinations of parameter values that do not fulfill constraints on the variables are excluded. This means that the method is capable of handling bounds on the adjustable parameters and fulfilling constraints.\n\nFor infinite number of iterations this method is guaranteed to find the global optimum of the objective function. In general one is interested in processing a very large number of iterations." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000472 ! global optimization algorithm
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000486 ! maximum iterations
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: skos:definition "Random search is an optimization method that attempts to find the optimum by testing the objective function's value on a series of combinations of random values of the adjustable parameters. The random values are generated complying with any boundaries selected by the user, furthermore, any combinations of parameter values that do not fulfill constraints on the variables are excluded. This means that the method is capable of handling bounds on the adjustable parameters and fulfilling constraints.\n\nFor infinite number of iterations this method is guaranteed to find the global optimum of the objective function. In general one is interested in processing a very large number of iterations." xsd:string
 
 [Term]
-id: KISAO_0000505
+id: kisao:KISAO_0000505
 name: particle swarm
-is_a: KISAO_0000472 ! global optimization algorithm
-property_value: definition "The particle swarm optimization method suggested by Kennedy and Eberhart is inspired by a flock of birds or a school of fish searching for food. Each particle has a position Xi and a velocity Vi in the parameter space. Additionally, it remembers its best achieved objective value O and position Mi. Dependent on its own information and the position of its best neighbor (a random subset of particles of the swarm) a new velocity is calculated. With this information the position is updated." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000472 ! global optimization algorithm
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000486 ! maximum iterations
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/doi/10.1109/ICNN.1995.488968" xsd:anyURI {comment="J. Kennedy and R. Eberhart. Particle Swarm Optimization. Proceedings of the Fourth IEEE International Conference on Neural Networks, Perth, Australia. 1942 - 1948. 1995."}
+property_value: skos:definition "The particle swarm optimization method suggested by Kennedy and Eberhart is inspired by a flock of birds or a school of fish searching for food. Each particle has a position Xi and a velocity Vi in the parameter space. Additionally, it remembers its best achieved objective value O and position Mi. Dependent on its own information and the position of its best neighbor (a random subset of particles of the swarm) a new velocity is calculated. With this information the position is updated." xsd:string
 
 [Term]
-id: KISAO_0000506
+id: kisao:KISAO_0000506
 name: genetic algorithm
-is_a: KISAO_0000520 ! evolutionary algorithm
-disjoint_from: KISAO_0000508 ! evolutionary programming
-property_value: altLabel "GA" xsd:string
-property_value: definition "The genetic algorithm (GA) is a computational technique that mimics evolution and is based on reproduction and selection. A GA is composed of individuals that reproduce and compete, each one is a potential solution to the (optimization) problem and is represented by a \"genome\" where each gene corresponds to one adjustable parameter. At each generation of the GA, each individual is paired with one other at random for reproduction. Two offspring are produced by combining their genomes and allowing for \"cross-over\", i.e., the two new individuals have genomes that are formed from a combination of the genomes of their parents. Also each new gene might have mutated, i.e. the parameter value might have changed slightly. At the end of the generation, the algorithm has double the number of individuals. Then each of the individuals is confronted with a number of others to count how many does it outperform (the number of wins is the number of these competitors that represent worse solutions than itself). All the individuals are ranked by their number of wins, and the population is again reduced to the original number of individuals by eliminating those which have worse fitness (solutions)." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000520 ! evolutionary algorithm
+disjoint_from: kisao:KISAO_0000508 ! evolutionary programming
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/isbn/9780750308953" xsd:anyURI {comment="T. Bäck, D.B. Fogel, and Z. Michalewicz. Handbook of evolutionary computation. Oxford: IOP Publishing/Oxford University Press. 1997."}
+property_value: skos:altLabel "GA" xsd:string
+property_value: skos:definition "The genetic algorithm (GA) is a computational technique that mimics evolution and is based on reproduction and selection. A GA is composed of individuals that reproduce and compete, each one is a potential solution to the (optimization) problem and is represented by a \"genome\" where each gene corresponds to one adjustable parameter. At each generation of the GA, each individual is paired with one other at random for reproduction. Two offspring are produced by combining their genomes and allowing for \"cross-over\", i.e., the two new individuals have genomes that are formed from a combination of the genomes of their parents. Also each new gene might have mutated, i.e. the parameter value might have changed slightly. At the end of the generation, the algorithm has double the number of individuals. Then each of the individuals is confronted with a number of others to count how many does it outperform (the number of wins is the number of these competitors that represent worse solutions than itself). All the individuals are ranked by their number of wins, and the population is again reduced to the original number of individuals by eliminating those which have worse fitness (solutions)." xsd:string
 
 [Term]
-id: KISAO_0000507
+id: kisao:KISAO_0000507
 name: genetic algorithm SR
-is_a: KISAO_0000506 ! genetic algorithm
-property_value: altLabel "genetic algorithm with stochastic ranking" xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000506 ! genetic algorithm
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/doi/10.1109/4235.873238" xsd:anyURI {comment="T. Runarsson and X. Yao. Stochastic ranking for constrained evolutionary optimization. EEE Transactions on Evolutionary Computation. 4. 284 - 294. 2000."}
+property_value: skos:altLabel "genetic algorithm with stochastic ranking" xsd:string
 
 [Term]
-id: KISAO_0000508
+id: kisao:KISAO_0000508
 name: evolutionary programming
-is_a: KISAO_0000520 ! evolutionary algorithm
-property_value: altLabel "EP" xsd:string
-property_value: definition "Evolutionary programming (EP) is a computational technique that mimics evolution and is based on reproduction and selection. An EP algorithm is composed of individuals that reproduce and compete, each one is a potential solution to the (optimization) problem and is represented by a \"genome\" where each gene corresponds to one adjustable parameter. At each generation of the EP, each individual reproduces asexually, i.e. divides into two individuals. One of these contains exactly the same \"genome\" as the parent while the other suffers some mutations (the parameter values of each gene change slightly). At the end of the generation, the algorithm has double the number of individuals. Then each of the individuals is confronted with a number of others to count how many does it outperform (the number of wins is the number of these competitors that represent worse solutions than itself). All the individuals are ranked by their number of wins, and the population is again reduced to the original number of individuals by eliminating those which have worse fitness (solutions)." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000520 ! evolutionary algorithm
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/isbn/9780750308953" xsd:anyURI {comment="T. Bäck, D.B. Fogel, and Z. Michalewicz. Handbook of evolutionary computation. Oxford: IOP Publishing/Oxford University Press. 1997."}
+property_value: skos:altLabel "EP" xsd:string
+property_value: skos:definition "Evolutionary programming (EP) is a computational technique that mimics evolution and is based on reproduction and selection. An EP algorithm is composed of individuals that reproduce and compete, each one is a potential solution to the (optimization) problem and is represented by a \"genome\" where each gene corresponds to one adjustable parameter. At each generation of the EP, each individual reproduces asexually, i.e. divides into two individuals. One of these contains exactly the same \"genome\" as the parent while the other suffers some mutations (the parameter values of each gene change slightly). At the end of the generation, the algorithm has double the number of individuals. Then each of the individuals is confronted with a number of others to count how many does it outperform (the number of wins is the number of these competitors that represent worse solutions than itself). All the individuals are ranked by their number of wins, and the population is again reduced to the original number of individuals by eliminating those which have worse fitness (solutions)." xsd:string
 
 [Term]
-id: KISAO_0000509
+id: kisao:KISAO_0000509
 name: evolutionary strategy
-is_a: KISAO_0000508 ! evolutionary programming
-property_value: altLabel "evolutionary strategies with stochastic ranking" xsd:string
-property_value: altLabel "SRES" xsd:string
-property_value: definition "Evolutionary Strategies with Stochastic Ranking (SRES) is similar to Evolutionary Programming. However, a parent has multiple offsprings during each generation. Each offspring will contain a recombination of genes with another parent and additional mutations. The algorithm assures that each parameter value will be within its boundaries. But constraints to the solutions may be violated." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000508 ! evolutionary programming
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/doi/10.1109/4235.873238" xsd:anyURI {comment="T. Runarsson and X. Yao. Stochastic ranking for constrained evolutionary optimization. EEE Transactions on Evolutionary Computation. 4. 284 - 294. 2000."}
+property_value: skos:altLabel "evolutionary strategies with stochastic ranking" xsd:string
+property_value: skos:altLabel "SRES" xsd:string
+property_value: skos:definition "Evolutionary Strategies with Stochastic Ranking (SRES) is similar to Evolutionary Programming. However, a parent has multiple offsprings during each generation. Each offspring will contain a recombination of genes with another parent and additional mutations. The algorithm assures that each parameter value will be within its boundaries. But constraints to the solutions may be violated." xsd:string
 
 [Term]
-id: KISAO_0000510
+id: kisao:KISAO_0000510
 name: truncated Newton
-is_a: KISAO_0000471 ! local optimization algorithm
-disjoint_from: KISAO_0000511 ! steepest descent
-property_value: definition "The Truncated Newton method is a sophisticated variant of the Newton optimization method. The Newton optimization method searches for the minimum of a nonlinear function by following descent directions determined from the function's first and second partial derivatives. The Truncated Newton method does an incomplete (truncated) solution of a system of linear equations to calculate the Newton direction. This means that the actual direction chosen for the descent is between the steepest descent direction and the true Newton direction." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000471 ! local optimization algorithm
+disjoint_from: kisao:KISAO_0000511 ! steepest descent
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/isbn/0122839528" xsd:anyURI {comment="P.E. Gill, W. Murray, and M.H. Wright. Practical Optimization. London, Academic Press. 1981."}
+property_value: skos:definition "The Truncated Newton method is a sophisticated variant of the Newton optimization method. The Newton optimization method searches for the minimum of a nonlinear function by following descent directions determined from the function's first and second partial derivatives. The Truncated Newton method does an incomplete (truncated) solution of a system of linear equations to calculate the Newton direction. This means that the actual direction chosen for the descent is between the steepest descent direction and the true Newton direction." xsd:string
 
 [Term]
-id: KISAO_0000511
+id: kisao:KISAO_0000511
 name: steepest descent
-is_a: KISAO_0000471 ! local optimization algorithm
-property_value: definition "Steepest descent is an optimization method that follows the direction of steepest descent on the hyper-surface of the objective function to find a local minimum. The direction of steepest descent is defined by the negative of the gradient of the objective function." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_a: kisao:KISAO_0000471 ! local optimization algorithm
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000209 ! relative tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000486 ! maximum iterations
+property_value: dc:creator "AZ" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1109/ACSSC.1991.186507" xsd:anyURI {comment="D.B. Fogel, L.J. Fogel, and J.W. Atmar. Meta-evolutionary programming. 25th Asiloma Conference on Signals, Systems and Computers. IEEE Computer Society, Asilomar . 540 - 545. 1992."}
+property_value: skos:definition "Steepest descent is an optimization method that follows the direction of steepest descent on the hyper-surface of the objective function to find a local minimum. The direction of steepest descent is defined by the negative of the gradient of the objective function." xsd:string
 
 [Term]
-id: KISAO_0000512
+id: kisao:KISAO_0000512
 name: praxis
-is_a: KISAO_0000471 ! local optimization algorithm
-property_value: definition "Praxis is a direct search method that searches for the minimum of a nonlinear function without requiring (or attempting to calculate) derivatives of that function. Praxis was developed by Brent after the method proposed by Powell. The inspiration for Praxis was the well-known method of minimising each adjustable parameter (direction) at a time - the principal axes method. In Praxis directions are chosen that do not coincide with the principal axes, in fact if the objective function is quadratic then these will be conjugate directions, assuring a fast convergence rate." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000471 ! local optimization algorithm
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000209 ! relative tolerance
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/isbn/0486419983" xsd:anyURI {comment="P.R. Brent. A new algorithm for minimizing a function of several variables without calculating derivatives. In Algorithms for minimization without derivatives, (Englewood Cliffs, NJ: Prentice-Hall, Inc.). 117 - 167. 1973."}
+property_value: skos:definition "Praxis is a direct search method that searches for the minimum of a nonlinear function without requiring (or attempting to calculate) derivatives of that function. Praxis was developed by Brent after the method proposed by Powell. The inspiration for Praxis was the well-known method of minimising each adjustable parameter (direction) at a time - the principal axes method. In Praxis directions are chosen that do not coincide with the principal axes, in fact if the objective function is quadratic then these will be conjugate directions, assuring a fast convergence rate." xsd:string
 
 [Term]
-id: KISAO_0000513
+id: kisao:KISAO_0000513
 name: NL2SOL
-is_a: KISAO_0000471 ! local optimization algorithm
-property_value: altLabel "adaptive nonlinear least-squares algorithm" xsd:string
-property_value: definition "The NL2SOL method is based on an adaptive nonlinear least-squares algorithm, devised by Dennis and colleagues. For problems with large number of residuals, this algorithm is known to be more reliable than Gauss-Newton or Levenberg-Marquardt method and more efficient than the secant or variable metric algorithms that are intended for general function minimization." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000471 ! local optimization algorithm
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000486 ! maximum iterations
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/doi/10.1145/355958.355966" xsd:anyURI {comment="J. E. Dennis, D. M. Gay, and R. E. Welsch. An adaptive nonlinear least-squares algorithm. ACM Trans. Math. Softw.. 7(3). 348 - 368. 1981."}
+property_value: skos:altLabel "adaptive nonlinear least-squares algorithm" xsd:string
+property_value: skos:definition "The NL2SOL method is based on an adaptive nonlinear least-squares algorithm, devised by Dennis and colleagues. For problems with large number of residuals, this algorithm is known to be more reliable than Gauss-Newton or Levenberg-Marquardt method and more efficient than the secant or variable metric algorithms that are intended for general function minimization." xsd:string
 
 [Term]
-id: KISAO_0000514
+id: kisao:KISAO_0000514
 name: Nelder-Mead
-is_a: KISAO_0000471 ! local optimization algorithm
-property_value: altLabel "simplex method" xsd:string
-property_value: definition "This method also known as the simplex method is due to Nelder and Mead. A simplex is a polytope of N+1 vertices in N dimensions. The objective function is evaluated at each vertex. Dependent on these calculated values a new simplex is constructed. The simplest step is to replace the worst point with a point reflected through the centroid of the remaining N points. If this point is better than the best current point, then we can try stretching exponentially out along this line. On the other hand, if this new point isn't much better than the previous value then we are stepping across a valley, so we shrink the simplex towards the best point." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000471 ! local optimization algorithm
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000211 ! absolute tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000486 ! maximum iterations
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/doi/10.1093/comjnl/7.4.308" xsd:anyURI {comment="J. A. Nelder and R. Mead. A simplex method for function minimization. Computer Journal. 7. 308 - 313. 1965."}
+property_value: skos:altLabel "simplex method" xsd:string
+property_value: skos:definition "This method also known as the simplex method is due to Nelder and Mead. A simplex is a polytope of N+1 vertices in N dimensions. The objective function is evaluated at each vertex. Dependent on these calculated values a new simplex is constructed. The simplest step is to replace the worst point with a point reflected through the centroid of the remaining N points. If this point is better than the best current point, then we can try stretching exponentially out along this line. On the other hand, if this new point isn't much better than the previous value then we are stepping across a valley, so we shrink the simplex towards the best point." xsd:string
 
 [Term]
-id: KISAO_0000515
+id: kisao:KISAO_0000515
 name: Levenberg-Marquardt
-is_a: KISAO_0000471 ! local optimization algorithm
-property_value: definition "Levenberg-Marquardt is a gradient descent method. It is a hybrid between the steepest descent and the Newton methods.\nLevenberg first suggested an improvement to the Newton method in order to make it more robust, i.e. to overcome the problem of non-convergence. His suggestion was to add a factor to the diagonal elements of the Hessian matrix of second derivatives when not close to the minimum (this can be judged by how positive definite the matrix is). The effect when this factor is large compared to the elements of Hessian is that the method then becomes the steepest descent method. Later Marquardt suggested that the factor should be multiplicative rather than additive and also defined a heuristic to make this factor increase or decrease. The method known as Levenberg-Marquardt is thus an adaptive method that effectively changes between the steepest descent to the Newton method." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000471 ! local optimization algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000322 ! hybridity
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000209 ! relative tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000486 ! maximum iterations
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/doi/10.1090/qam/10666" xsd:anyURI {comment="K. Levenberg. A method for the solution of certain nonlinear problems in least squares. Quart. Appl. Math.. 2. 164 - 168. 1944."}
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0111030" xsd:anyURI {comment="D.W. Marquardt. An algorithm for least squares estimation of nonlinear parameters. SIAM Journal. 11. 431 - 441. 1963."}
+property_value: skos:definition "Levenberg-Marquardt is a gradient descent method. It is a hybrid between the steepest descent and the Newton methods.\nLevenberg first suggested an improvement to the Newton method in order to make it more robust, i.e. to overcome the problem of non-convergence. His suggestion was to add a factor to the diagonal elements of the Hessian matrix of second derivatives when not close to the minimum (this can be judged by how positive definite the matrix is). The effect when this factor is large compared to the elements of Hessian is that the method then becomes the steepest descent method. Later Marquardt suggested that the factor should be multiplicative rather than additive and also defined a heuristic to make this factor increase or decrease. The method known as Levenberg-Marquardt is thus an adaptive method that effectively changes between the steepest descent to the Newton method." xsd:string
 
 [Term]
-id: KISAO_0000516
+id: kisao:KISAO_0000516
 name: Hooke&Jeeves
-is_a: KISAO_0000471 ! local optimization algorithm
-property_value: altLabel "Hooke and Jeeves method" xsd:string
-property_value: altLabel "Hooke-Jeeves method" xsd:string
-property_value: altLabel "method of Hooke and Jeeves" xsd:string
-property_value: definition "The method of Hooke and Jeeves is a direct search algorithm that searches for the minimum of a nonlinear function without requiring (or attempting to calculate) derivatives of the function. Instead it is based on a heuristic that suggests a descent direction using the values of the function calculated in a number of previous iterations." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000471 ! local optimization algorithm
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000209 ! relative tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000486 ! maximum iterations
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/doi/10.1145/321062.321069" xsd:anyURI {comment="R. Hooke and T. A. Jeeves. \"Direct search\" solution of numerical and statistical problems. Journal of the Association for Computing Machinery. 8. 212 - 229. 1961."}
+property_value: skos:altLabel "Hooke and Jeeves method" xsd:string
+property_value: skos:altLabel "Hooke-Jeeves method" xsd:string
+property_value: skos:altLabel "method of Hooke and Jeeves" xsd:string
+property_value: skos:definition "The method of Hooke and Jeeves is a direct search algorithm that searches for the minimum of a nonlinear function without requiring (or attempting to calculate) derivatives of the function. Instead it is based on a heuristic that suggests a descent direction using the values of the function calculated in a number of previous iterations." xsd:string
 
 [Term]
-id: KISAO_0000520
+id: kisao:KISAO_0000517
+name: number of generations
+is_a: kisao:KISAO_0000518 ! evolutionary algorithm parameter
+disjoint_from: kisao:KISAO_0000519 ! population size
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "The parameter is a positive integer value to determine the number of generations the evolutionary algorithm shall evolve the population." xsd:string
+
+[Term]
+id: kisao:KISAO_0000518
+name: evolutionary algorithm parameter
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000520 ! evolutionary algorithm
+property_value: dc:creator "AZ" xsd:string
+
+[Term]
+id: kisao:KISAO_0000519
+name: population size
+is_a: kisao:KISAO_0000518 ! evolutionary algorithm parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "The parameter is a positive integer value to determine the size of the population, i.e., the number of individuals that survive after each generation." xsd:string
+
+[Term]
+id: kisao:KISAO_0000520
 name: evolutionary algorithm
-is_a: KISAO_0000472 ! global optimization algorithm
-property_value: definition "An optimisation algorithm that mimics evolution and is based on reproduction and selection." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isOrganizational "true" xsd:string
+is_a: kisao:KISAO_0000472 ! global optimization algorithm
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000517 ! number of generations
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000519 ! population size
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:string
+property_value: skos:definition "An optimisation algorithm that mimics evolution and is based on reproduction and selection." xsd:string
 
 [Term]
-id: KISAO_0000524
+id: kisao:KISAO_0000521
+name: simulated annealing parameter
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000503 ! simulated annealing
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+
+[Term]
+id: kisao:KISAO_0000522
+name: start temperature
+is_a: kisao:KISAO_0000521 ! simulated annealing parameter
+disjoint_from: kisao:KISAO_0000523 ! cooling factor
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "Initial temperature of the system. The higher the temperature, the larger the probability that a global optimum is found. Note that the temperature should be very high in the beginning of the method (the system should be above the \"melting\" temperature). This value has the same units as the objective function, so what represents \"high\" is different from problem to problem." xsd:string
+
+[Term]
+id: kisao:KISAO_0000523
+name: cooling factor
+is_a: kisao:KISAO_0000521 ! simulated annealing parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "Rate by which the temperature is reduced from one cycle to the next, given by the formula: Tnew=Told*\"Cooling Factor\". The simulated annealing algorithm works best if the temperature is reduced at a slow rate, so this value should be close to 1." xsd:string
+
+[Term]
+id: kisao:KISAO_0000524
 name: partitioned leaping method
-is_a: KISAO_0000039 ! tau-leaping method
-property_value: definition "Multiscale simulation approach for modeling stochasticity in chemical reaction networks. The approach seamlessly integrates exact-stochastic and \"leaping\" methodologies into a single partitioned leaping algorithmic framework. The technique correctly accounts for stochastic noise at significantly reduced computational cost, requires the definition of only three modelindependent parameters and is particularly well-suited for simulating systems containing widely disparate species populations." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/bionetgen" xsd:anyURI {comment="BioNetGen"}
+is_a: kisao:KISAO_0000039 ! tau-leaping method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000488 ! seed
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/bionetgen" xsd:anyURI {comment="BioNetGen"}
 property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2354085" xsd:anyURI {comment="Harris LA, Clancy P. A \"partitioned leaping\" approach for multiscale modeling of chemical reaction dynamics. J Chem Phys. 125 (14), 144107 (2006)."}
+property_value: skos:definition "Multiscale simulation approach for modeling stochasticity in chemical reaction networks. The approach seamlessly integrates exact-stochastic and \"leaping\" methodologies into a single partitioned leaping algorithmic framework. The technique correctly accounts for stochastic noise at significantly reduced computational cost, requires the definition of only three modelindependent parameters and is particularly well-suited for simulating systems containing widely disparate species populations." xsd:string
 
 [Term]
-id: KISAO_0000526
+id: kisao:KISAO_0000525
+name: stop condition
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/bionetgen" xsd:anyURI {comment="BioNetGen"}
+property_value: skos:definition "A condition upon which a simulation should terminate." xsd:string
+
+[Term]
+id: kisao:KISAO_0000526
 name: flux variability analysis
-is_a: KISAO_0000407 ! steady state method
-is_a: KISAO_0000622 ! flux balance method
-property_value: altLabel "FVA" xsd:string
-property_value: definition "Method for determining the minimum and maximum flux of each reaction that satisfies the flux constraints of the flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/cobrapy" xsd:anyURI {comment="COBRApy"}
+is_a: kisao:KISAO_0000622 ! flux balance method
+is_a: kisao:KISAO_0000630 ! general steady state method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000529 ! parallelism
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000531 ! fraction of optimum
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000532 ! loopless
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000534 ! reactions
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000578 ! nested algorithm
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cobrapy" xsd:anyURI {comment="COBRApy"}
 property_value: seeAlso "http://identifiers.org/doi/10.1016/j.ymben.2003.09.002" xsd:anyURI {comment="Mahadevan R, Schilling CH. The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. Metab Eng. 2003;5(4):264-276."}
+property_value: skos:altLabel "FVA" xsd:string
+property_value: skos:definition "Method for determining the minimum and maximum flux of each reaction that satisfies the flux constraints of the flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model." xsd:string
 
 [Term]
-id: KISAO_0000527
+id: kisao:KISAO_0000527
 name: geometric flux balance analysis
-is_a: KISAO_0000437 ! flux balance analysis
-disjoint_from: KISAO_0000591 ! mdFBA
-property_value: altLabel "geometric FBA" xsd:string
-property_value: altLabel "gFBA" xsd:string
-property_value: definition "Method for determining the central flux distribution among all flux distributions that satisfy the constraints of the  flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/cobrapy" xsd:anyURI {comment="COBRApy"}
+is_a: kisao:KISAO_0000437 ! flux balance analysis
+disjoint_from: kisao:KISAO_0000591 ! mdFBA
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000529 ! parallelism
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cobrapy" xsd:anyURI {comment="COBRApy"}
 property_value: seeAlso "http://identifiers.org/doi/10.1016/j.jtbi.2009.01.027" xsd:anyURI {comment="Smallbone K, Simeonidis E. Flux balance analysis: a geometric perspective. J Theor Biol. 2009;258(2):311-315."}
+property_value: skos:altLabel "geometric FBA" xsd:string
+property_value: skos:altLabel "gFBA" xsd:string
+property_value: skos:definition "Method for determining the central flux distribution among all flux distributions that satisfy the constraints of the  flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model." xsd:string
 
 [Term]
-id: KISAO_0000528
+id: kisao:KISAO_0000528
 name: parsimonious enzyme usage flux balance analysis (minimum sum of absolute fluxes)
-is_a: KISAO_0000620 ! parsimonius flux balance analysis
-disjoint_from: KISAO_0000554 ! parsimonius flux balance analysis (minimum number of active fluxes)
-property_value: altLabel "parsimonious FBA" xsd:string
-property_value: altLabel "parsimonious flux balance analysis" xsd:string
-property_value: altLabel "pFBA" xsd:string
-property_value: definition "Method for determining the smallest flux distribution among all flux distributions that satisfy the constraints of the flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/cbmpy" xsd:anyURI {comment="CBMPy"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/cobrapy" xsd:anyURI {comment="COBRApy"}
+is_a: kisao:KISAO_0000620 ! parsimonius flux balance analysis
+disjoint_from: kisao:KISAO_0000554 ! parsimonius flux balance analysis (minimum number of active fluxes)
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000531 ! fraction of optimum
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000533 ! pFBA factor
+property_value: dc:creator "AZ" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cbmpy" xsd:anyURI {comment="CBMPy"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cobrapy" xsd:anyURI {comment="COBRApy"}
 property_value: seeAlso "http://identifiers.org/doi/10.1038/msb.2010.47" xsd:anyURI {comment="Lewis NE, Hixson KK, Conrad TM, et al. Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models. Mol Syst Biol. 2010;6:390."}
+property_value: skos:altLabel "parsimonious FBA" xsd:string
+property_value: skos:altLabel "parsimonious flux balance analysis" xsd:string
+property_value: skos:altLabel "pFBA" xsd:string
+property_value: skos:definition "Method for determining the smallest flux distribution among all flux distributions that satisfy the constraints of the flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model." xsd:string
+
+[Term]
+id: kisao:KISAO_0000529
+name: parallelism
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000526 ! flux variability analysis
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000527 ! geometric flux balance analysis
+property_value: skos:definition "Number of parallel processes to use." xsd:string
+
+[Term]
+id: kisao:KISAO_0000531
+name: fraction of optimum
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000526 ! flux variability analysis
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000528 ! parsimonious enzyme usage flux balance analysis (minimum sum of absolute fluxes)
+property_value: skos:definition "Fraction of the optimum solution which must be maintained." xsd:string
 
 [Term]
-id: KISAO_0000535
+id: kisao:KISAO_0000532
+name: loopless
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000526 ! flux variability analysis
+property_value: skos:definition "Whether to return only loopless flux solutions." xsd:string
+
+[Term]
+id: kisao:KISAO_0000533
+name: pFBA factor
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000528 ! parsimonious enzyme usage flux balance analysis (minimum sum of absolute fluxes)
+property_value: skos:definition "Maximum permissible sum of absolute fluxes." xsd:string
+
+[Term]
+id: kisao:KISAO_0000534
+name: reactions
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+relationship: kisao:KISAO_0000250 kisao:KISAO_0000526 ! flux variability analysis
+property_value: skos:definition "FVA algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000526] parameter: reactions to compute the variablity of." xsd:string
+
+[Term]
+id: kisao:KISAO_0000535
 name: VODE
-is_a: KISAO_0000433 ! CVODE-like method
-relationship: KISAO_0000359 KISAO_0000019 {maxCardinality="1"} ! CVODE
-property_value: altLabel "DVODE" xsd:string {comment="RELATED"}
-property_value: altLabel "Real-valued Variable-coefficient Ordinary Differential Equation solver, with fixed-leading-coefficient implementation" xsd:string {comment="EXACT"}
-property_value: altLabel "real-valued variable-coefficient ordinary differential equation solver, with fixed-leading-coefficient implementation" xsd:string
-property_value: definition "VODE provides implicit Adams method (for non-stiff problems) and a method based on backward differentiation formulas (BDF) (for stiff problems)." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "deSolve" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
-property_value: isImplementedIn "Odespy" xsd:string
-property_value: isImplementedIn "SciPy" xsd:string
+is_a: kisao:KISAO_0000433 ! CVODE-like method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000542 {maxCardinality="1"} ! correction step should use internally generated full Jacobian
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000019 {maxCardinality="1"} ! CVODE
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "deSolve" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
+property_value: kisao:isImplementedIn "Odespy" xsd:string
+property_value: kisao:isImplementedIn "SciPy" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0910062" xsd:anyURI {comment="Peter N. Brown, George D. Byrne & Alan C. Hindmarsh. VODE: A Variable-Coefficient ODE Solver. SIAM J. Sci. and Stat. Comput., 10(5), 1038–1051 (1988)."}
+property_value: skos:altLabel "DVODE" xsd:string {comment="RELATED"}
+property_value: skos:altLabel "Real-valued Variable-coefficient Ordinary Differential Equation solver, with fixed-leading-coefficient implementation" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "real-valued variable-coefficient ordinary differential equation solver, with fixed-leading-coefficient implementation" xsd:string
+property_value: skos:definition "VODE provides implicit Adams method (for non-stiff problems) and a method based on backward differentiation formulas (BDF) (for stiff problems)." xsd:string
 
 [Term]
-id: KISAO_0000536
+id: kisao:KISAO_0000536
 name: ZVODE
-is_a: KISAO_0000433 ! CVODE-like method
-relationship: KISAO_0000359 KISAO_0000019 {maxCardinality="1"} ! CVODE
-property_value: altLabel "Complex-valued Variable-coefficient Ordinary Differential Equation solver, with fixed-leading-coefficient implementation" xsd:string {comment="EXACT"}
-property_value: altLabel "complex-valued variable-coefficient ordinary differential equation solver, with fixed-leading-coefficient implementation" xsd:string
-property_value: definition "ZVODE provides implicit Adams method (for non-stiff problems) and a method based on backward differentiation formulas (BDF) (for stiff problems)." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "deSolve" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
-property_value: isImplementedIn "Odespy" xsd:string
-property_value: isImplementedIn "SciPy" xsd:string
+is_a: kisao:KISAO_0000433 ! CVODE-like method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000542 {maxCardinality="1"} ! correction step should use internally generated full Jacobian
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000019 {maxCardinality="1"} ! CVODE
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "deSolve" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
+property_value: kisao:isImplementedIn "Odespy" xsd:string
+property_value: kisao:isImplementedIn "SciPy" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0910062" xsd:anyURI {comment="Peter N. Brown, George D. Byrne & Alan C. Hindmarsh. VODE: A Variable-Coefficient ODE Solver. SIAM J. Sci. and Stat. Comput., 10(5), 1038–1051 (1988)."}
+property_value: skos:altLabel "Complex-valued Variable-coefficient Ordinary Differential Equation solver, with fixed-leading-coefficient implementation" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "complex-valued variable-coefficient ordinary differential equation solver, with fixed-leading-coefficient implementation" xsd:string
+property_value: skos:definition "ZVODE provides implicit Adams method (for non-stiff problems) and a method based on backward differentiation formulas (BDF) (for stiff problems)." xsd:string
 
 [Term]
-id: KISAO_0000537
+id: kisao:KISAO_0000537
 name: explicit Runge-Kutta method of order 3(2)
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: altLabel "RK23" xsd:string {comment="EXACT"}
-property_value: definition "RK23 uses the Bogacki-Shampine pair of formulas [1]. The error is controlled assuming accuracy of the second-order method, but steps are taken using the third-order accurate formula (local extrapolation is done). A cubic Hermite polynomial is used for the dense output." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "deSolve" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
-property_value: isImplementedIn "MATLAB" xsd:string
-property_value: isImplementedIn "Octave" xsd:string
-property_value: isImplementedIn "Odespy" xsd:string
-property_value: isImplementedIn "SciPy" xsd:string
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "deSolve" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
+property_value: kisao:isImplementedIn "MATLAB" xsd:string
+property_value: kisao:isImplementedIn "Octave" xsd:string
+property_value: kisao:isImplementedIn "Odespy" xsd:string
+property_value: kisao:isImplementedIn "SciPy" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1016/0893-9659(89)90079-7" xsd:anyURI {comment="P. Bogacki & L. F. Shampine. A 3(2) pair of Runge - Kutta formulas. Applied Mathematics Letters 2(4), 321-325 (1989)."}
-
-[Term]
-id: KISAO_0000544
+property_value: skos:altLabel "RK23" xsd:string {comment="EXACT"}
+property_value: skos:definition "RK23 uses the Bogacki-Shampine pair of formulas [1]. The error is controlled assuming accuracy of the second-order method, but steps are taken using the third-order accurate formula (local extrapolation is done). A cubic Hermite polynomial is used for the dense output." xsd:string
+
+[Term]
+id: kisao:KISAO_0000538
+name: safety factor on new step selection
+is_a: kisao:KISAO_0000242 ! error control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
+property_value: kisao:isImplementedIn "JModelica" xsd:string
+property_value: kisao:isImplementedIn "Odespy" xsd:string
+property_value: kisao:isImplementedIn "SciPy" xsd:string
+property_value: skos:altLabel "safe" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "safety" xsd:string {comment="EXACT"}
+
+[Term]
+id: kisao:KISAO_0000539
+name: minimum factor to change step size by
+is_a: kisao:KISAO_0000242 ! error control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
+property_value: kisao:isImplementedIn "JModelica" xsd:string
+property_value: kisao:isImplementedIn "Odespy" xsd:string
+property_value: kisao:isImplementedIn "SciPy" xsd:string
+property_value: skos:altLabel "dfactor" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "fac1" xsd:string {comment="EXACT"}
+property_value: skos:definition "Minimum factor to increase/decrease step size by in one step. The new step-size is chosen subject to the restriction fac1 <= current step-size / old step-size <= fac2." xsd:string
+
+[Term]
+id: kisao:KISAO_0000540
+name: maximum factor to change step size by
+is_a: kisao:KISAO_0000242 ! error control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
+property_value: kisao:isImplementedIn "JModelica" xsd:string
+property_value: kisao:isImplementedIn "Odespy" xsd:string
+property_value: kisao:isImplementedIn "SciPy" xsd:string
+property_value: skos:altLabel "fac2" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "ifactor" xsd:string {comment="EXACT"}
+property_value: skos:definition "Maximum factor to increase/decrease step size by in one step. The new step-size is chosen subject to the restriction fac1 <= current step-size / old step-size <= fac2." xsd:string
+
+[Term]
+id: kisao:KISAO_0000541
+name: beta parameter for stabilized step size control
+is_a: kisao:KISAO_0000242 ! error control parameter
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
+property_value: kisao:isImplementedIn "JModelica" xsd:string
+property_value: kisao:isImplementedIn "Odespy" xsd:string
+property_value: kisao:isImplementedIn "SciPy" xsd:string
+property_value: skos:altLabel "beta" xsd:string {comment="EXACT"}
+
+[Term]
+id: kisao:KISAO_0000542
+name: correction step should use internally generated full Jacobian
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
+property_value: kisao:isImplementedIn "SciPy" xsd:string
+property_value: skos:altLabel "MF=22" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "with Jacobian" xsd:string {comment="EXACT"}
+property_value: skos:definition "Specifies whether the iteration method of the ODE solver’s correction step is chord iteration with an internally generated full Jacobian or functional iteration with no Jacobian. Option is only considered when the user has not supplied a Jacobian function and has not indicated (by setting either upper or lower band) that the Jacobian is banded." xsd:string
+
+[Term]
+id: kisao:KISAO_0000543
+name: stability limit detection flag
+is_a: kisao:KISAO_0000242 ! error control parameter
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "SUNDIALS" xsd:string
+property_value: skos:definition "Flag to activate stability limit detection." xsd:string
+
+[Term]
+id: kisao:KISAO_0000544
 name: IDAS
-is_a: KISAO_0000432 ! IDA-like method
-property_value: altLabel "implicit differential-algebraic solver with sensitivity analysis" xsd:string {comment="EXACT"}
-property_value: definition "IDAS solves real differential-algebraic systems in N-space, in the general form F(t,y,y')=0, y(t0)=y0, y'(t0)=y'0 with sensitivity analysis." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "SUNDIALS" xsd:string
+is_a: kisao:KISAO_0000432 ! IDA-like method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000545 {maxCardinality="1"} ! include sensitivity variables in error control mechanism
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "SUNDIALS" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1145/1089014.1089020" xsd:anyURI {comment="SUNDIALS: Suite of nonlinear and differential/algebraic equation solvers. Alan C. Hindmarsh, Peter N. Brown, Keith E. Grant, Steven L. Lee, Radu Serban, Dana E. Shumaker & Carol S. Woodward. ACM Transactions on Mathematical Software 31(3), 363-396 (2005)."}
+property_value: skos:altLabel "implicit differential-algebraic solver with sensitivity analysis" xsd:string {comment="EXACT"}
+property_value: skos:definition "IDAS solves real differential-algebraic systems in N-space, in the general form F(t,y,y')=0, y(t0)=y0, y'(t0)=y'0 with sensitivity analysis." xsd:string
+
+[Term]
+id: kisao:KISAO_0000545
+name: include sensitivity variables in error control mechanism
+is_a: kisao:KISAO_0000242 ! error control parameter
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "SUNDIALS" xsd:string
+property_value: skos:altLabel "errconS" xsd:string {comment="EXACT"}
+property_value: skos:definition "Specifies whether sensitivity variables are included or not in the error control mechanism." xsd:string
 
 [Term]
-id: KISAO_0000546
+id: kisao:KISAO_0000546
 name: convex optimization algorithm
-is_a: KISAO_0000472 ! global optimization algorithm
-property_value: definition "Optimization of a convex function over a convex set. Convex optimization is subclass of global optimization because conveness gaurantees that each local optimum is a global optimum." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+is_a: kisao:KISAO_0000472 ! global optimization algorithm
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Optimization of a convex function over a convex set. Convex optimization is subclass of global optimization because conveness gaurantees that each local optimum is a global optimum." xsd:string
 
 [Term]
-id: KISAO_0000547
+id: kisao:KISAO_0000547
 name: linear programming
-is_a: KISAO_0000546 ! convex optimization algorithm
-property_value: altLabel "LP" xsd:string {comment="EXACT"}
-property_value: definition "Method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "ConvOpt" xsd:string
-property_value: isImplementedIn "CPLEX" xsd:string
-property_value: isImplementedIn "CVXOPT" xsd:string
-property_value: isImplementedIn "GLPK" xsd:string
-property_value: isImplementedIn "Gurobi" xsd:string
-property_value: isImplementedIn "MATLAB" xsd:string
-property_value: isImplementedIn "Mosek" xsd:string
-property_value: isImplementedIn "OptLang" xsd:string
-property_value: isImplementedIn "SciPy" xsd:string
-property_value: isImplementedIn "SoPlex" xsd:string
-property_value: isImplementedIn "XPRESS" xsd:string
-
-[Term]
-id: KISAO_0000548
+is_a: kisao:KISAO_0000546 ! convex optimization algorithm
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "ConvOpt" xsd:string
+property_value: kisao:isImplementedIn "CPLEX" xsd:string
+property_value: kisao:isImplementedIn "CVXOPT" xsd:string
+property_value: kisao:isImplementedIn "GLPK" xsd:string
+property_value: kisao:isImplementedIn "Gurobi" xsd:string
+property_value: kisao:isImplementedIn "MATLAB" xsd:string
+property_value: kisao:isImplementedIn "Mosek" xsd:string
+property_value: kisao:isImplementedIn "OptLang" xsd:string
+property_value: kisao:isImplementedIn "SciPy" xsd:string
+property_value: kisao:isImplementedIn "SoPlex" xsd:string
+property_value: kisao:isImplementedIn "XPRESS" xsd:string
+property_value: skos:altLabel "LP" xsd:string {comment="EXACT"}
+property_value: skos:definition "Method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships." xsd:string
+
+[Term]
+id: kisao:KISAO_0000548
 name: quadratic programming
-is_a: KISAO_0000549 ! non-linear programming
-property_value: altLabel "QP" xsd:string {comment="EXACT"}
-property_value: definition "Process of solving a quadratic optimization problem." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "ConvOpt" xsd:string
-property_value: isImplementedIn "CPLEX" xsd:string
-property_value: isImplementedIn "CVXOPT" xsd:string
-property_value: isImplementedIn "Gurobi" xsd:string
-property_value: isImplementedIn "MATLAB" xsd:string
-property_value: isImplementedIn "Mosek" xsd:string
-property_value: isImplementedIn "OptLang" xsd:string
-property_value: isImplementedIn "XPRESS" xsd:string
-
-[Term]
-id: KISAO_0000549
+is_a: kisao:KISAO_0000549 ! non-linear programming
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "ConvOpt" xsd:string
+property_value: kisao:isImplementedIn "CPLEX" xsd:string
+property_value: kisao:isImplementedIn "CVXOPT" xsd:string
+property_value: kisao:isImplementedIn "Gurobi" xsd:string
+property_value: kisao:isImplementedIn "MATLAB" xsd:string
+property_value: kisao:isImplementedIn "Mosek" xsd:string
+property_value: kisao:isImplementedIn "OptLang" xsd:string
+property_value: kisao:isImplementedIn "XPRESS" xsd:string
+property_value: skos:altLabel "QP" xsd:string {comment="EXACT"}
+property_value: skos:definition "Process of solving a quadratic optimization problem." xsd:string
+
+[Term]
+id: kisao:KISAO_0000549
 name: non-linear programming
-is_a: KISAO_0000472 ! global optimization algorithm
-property_value: definition "Process of solving an optimization problem where some of the constraints or the objective function are nonlinear." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+is_a: kisao:KISAO_0000472 ! global optimization algorithm
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Process of solving an optimization problem where some of the constraints or the objective function are nonlinear." xsd:string
 
 [Term]
-id: KISAO_0000550
+id: kisao:KISAO_0000550
 name: simplex method
-is_a: KISAO_0000547 ! linear programming
-property_value: altLabel "Dantzig's simplex algorithm" xsd:string {comment="EXACT"}
-property_value: definition "Approach to solving linear programming models by hand using slack variables, tableaus, and pivot variables as a means to finding the optimal solution of an optimization problem." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "CPLEX" xsd:string
-property_value: isImplementedIn "GLPK" xsd:string
-property_value: isImplementedIn "Gurobi" xsd:string
+is_a: kisao:KISAO_0000547 ! linear programming
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "CPLEX" xsd:string
+property_value: kisao:isImplementedIn "GLPK" xsd:string
+property_value: kisao:isImplementedIn "Gurobi" xsd:string
 property_value: seeAlso "https://projecteuclid.org/euclid.pjm/1103044531" xsd:anyURI
+property_value: skos:altLabel "Dantzig's simplex algorithm" xsd:string {comment="EXACT"}
+property_value: skos:definition "Approach to solving linear programming models by hand using slack variables, tableaus, and pivot variables as a means to finding the optimal solution of an optimization problem." xsd:string
 
 [Term]
-id: KISAO_0000551
+id: kisao:KISAO_0000551
 name: primal-dual interior point method
-is_a: KISAO_0000547 ! linear programming
-property_value: definition "The Interior Point method approximates the constraints of a linear programming model as a set of boundaries surrounding a region." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "CPLEX" xsd:string
-property_value: isImplementedIn "GLPK" xsd:string
-property_value: isImplementedIn "Gurobi" xsd:string
+is_a: kisao:KISAO_0000547 ! linear programming
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "CPLEX" xsd:string
+property_value: kisao:isImplementedIn "GLPK" xsd:string
+property_value: kisao:isImplementedIn "Gurobi" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1137/0802028" xsd:anyURI {comment="Sanjay Mehrotra. On the Implementation of a Primal-Dual Interior Point Method. SIAM Journal on Optimization, 2(4), 575–601(1991)."}
+property_value: skos:definition "The Interior Point method approximates the constraints of a linear programming model as a set of boundaries surrounding a region." xsd:string
 
 [Term]
-id: KISAO_0000554
-name: parsimonius flux balance analysis (minimum number of active fluxes)
-is_a: KISAO_0000620 ! parsimonius flux balance analysis
-property_value: altLabel "parsimonious FBA" xsd:string
-property_value: altLabel "parsimonious flux balance analysis" xsd:string
-property_value: altLabel "pFBA" xsd:string
-property_value: definition "A technique for selecting a parsimonious flux distribution which has a minimal number of active fluxes." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/cbmpy" xsd:anyURI {comment="CBMPy"}
+id: kisao:KISAO_0000552
+name: optimization method
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "CPLEX" xsd:string
+property_value: kisao:isImplementedIn "GLPK" xsd:string
+property_value: kisao:isImplementedIn "Gurobi" xsd:string
+property_value: skos:definition "Optimization method such as the revised simplex method [http://identifiers.org/biomodels.kisao/KISAO_0000550] or primal-dual interior point method [http://identifiers.org/biomodels.kisao/KISAO_0000551]." xsd:string
+
+[Term]
+id: kisao:KISAO_0000553
+name: optimization solver
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "ConvOpt" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cbmpy" xsd:anyURI {comment="CBMPy"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cobrapy" xsd:anyURI {comment="COBRApy"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/raven" xsd:anyURI {comment="RAVEN"}
+property_value: kisao:isImplementedIn "OptLang" xsd:string
+property_value: skos:definition "Optimization solver such as CPLEX, GLPK, or Gurobi." xsd:string
 
 [Term]
-id: KISAO_0000560
+id: kisao:KISAO_0000554
+name: parsimonius flux balance analysis (minimum number of active fluxes)
+is_a: kisao:KISAO_0000620 ! parsimonius flux balance analysis
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cbmpy" xsd:anyURI {comment="CBMPy"}
+property_value: skos:altLabel "parsimonious FBA" xsd:string
+property_value: skos:altLabel "parsimonious flux balance analysis" xsd:string
+property_value: skos:altLabel "pFBA" xsd:string
+property_value: skos:definition "A technique for selecting a parsimonious flux distribution which has a minimal number of active fluxes." xsd:string
+
+[Term]
+id: kisao:KISAO_0000555
+name: absolute quadrature tolerance
+is_a: kisao:KISAO_0000211 ! absolute tolerance
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/amici" xsd:anyURI {comment="AMICI"}
+property_value: kisao:isImplementedIn "SUNDIALS" xsd:string
+property_value: skos:definition "Absolute error tolerance of the adjoint solution." xsd:string
+
+[Term]
+id: kisao:KISAO_0000556
+name: relative quadrature tolerance
+is_a: kisao:KISAO_0000209 ! relative tolerance
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/amici" xsd:anyURI {comment="AMICI"}
+property_value: kisao:isImplementedIn "SUNDIALS" xsd:string
+property_value: skos:definition "Relative error tolerance of the adjoint solution." xsd:string
+
+[Term]
+id: kisao:KISAO_0000557
+name: absolute steady-state tolerance
+is_a: kisao:KISAO_0000211 ! absolute tolerance
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/amici" xsd:anyURI {comment="AMICI"}
+property_value: kisao:isImplementedIn "SUNDIALS" xsd:string
+property_value: skos:definition "Absolute error tolerance of the steady-state." xsd:string
+
+[Term]
+id: kisao:KISAO_0000558
+name: relative steady-state tolerance
+is_a: kisao:KISAO_0000209 ! relative tolerance
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/amici" xsd:anyURI {comment="AMICI"}
+property_value: kisao:isImplementedIn "SUNDIALS" xsd:string
+property_value: skos:definition "Relative error tolerance of the steady-state." xsd:string
+
+[Term]
+id: kisao:KISAO_0000559
+name: initial step size
+is_a: kisao:KISAO_0000242 ! error control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: kisao:isImplementedIn "libRoadRunner" xsd:string
+property_value: kisao:isImplementedIn "SciPy" xsd:string
+property_value: kisao:isImplementedIn "SUNDIALS" xsd:string
+property_value: skos:definition "Initial time step size." xsd:string
+
+[Term]
+id: kisao:KISAO_0000560
 name: LSODA/LSODAR hybrid method
-is_a: KISAO_0000094 ! Livermore solver
-property_value: definition "Automatically use LSODA or LSODAR as apropriate for the given problem. Use LSODA if the problem has no roots. Use LSODAR if the problem has roots." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000094 ! Livermore solver
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/doi/10.1007/978-1-59745-525-1_2" xsd:anyURI {comment="Pedro Mendes, Stefan Hoops, Sven Sahle, Ralph Gauges, Joseph Dada & Ursula Kummer. Computational modeling of biochemical networks using COPASI. Methods in Molecular Biology 500, 17–59 (2009)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1016/j.jbiotec.2017.06.1200" xsd:anyURI {comment="Frank T. Bergmann, Stefan Hoops, Brian Klahn, Ursula Kummer, Pedro Mendes Jürgen Pahle & Sven Sahle. COPASI and its applications in biotechnology. Journal of Biotechnology 261, 215–220 (2017)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1093/bioinformatics/btl485" xsd:anyURI {comment="Stefan Hoops, Sven Sahle, Ralph Gauges, Christine Lee, Jürgen Pahle, Natalia Simus, Mudita Singhal, Liang Xu, Pedro Mendes & Ursula Kummer. COPASI—a complex pathway simulator. Bioinformatics 22 (24), 3067–3074 (2006)."}
 property_value: seeAlso "http://identifiers.org/doi/10.5555/1218112.1218421" xsd:anyURI {comment="Sven Sahle, Ralph Gauges, Jürgen Pahle, Natalia Simus, Ursula Kummer, Stefan Hoops, Christine Lee, Mudita Singhal, Liang Xu & Pedro Mendes. Simulation of biochemical networks using COPASI—a complex pathway simulator. Proceedings of the 2006 Winter Simulation Conference, Monterey, CA, USA, 1698–1706 (2006)."}
+property_value: skos:definition "Automatically use LSODA or LSODAR as apropriate for the given problem. Use LSODA if the problem has no roots. Use LSODAR if the problem has roots." xsd:string
 
 [Term]
-id: KISAO_0000561
+id: kisao:KISAO_0000561
 name: Pahle hybrid Gibson-Bruck Next Reaction method/Runge-Kutta method
-is_a: KISAO_0000231 ! Pahle hybrid method
-disjoint_from: KISAO_0000562 ! Pahle hybrid Gibson-Bruck Next Reaction method/LSODA method
-property_value: definition "Combines a deterministic numerical integration of ODEs with a stochastic simulation algorithm. The whole biochemical network is partitioned into a deterministic and a stochastic subnet internally. The deterministic subnet contains all reactions in which only species with high particle numbers take part. All reactions with at least one low-numbered species are in the stochastic subnet. The partitioning of the biochemical network can change dynamically during the simulation. The reaction probabilities of the stochastic subnet are approximated as constant during one stochastic step. A 4th-order Runge-Kutta method is used to numerically integrate the deterministic part of the system. The stochastic subnet is simulated by the Gibson-Bruck Next Reaction Method." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000231 ! Pahle hybrid method
+disjoint_from: kisao:KISAO_0000562 ! Pahle hybrid Gibson-Bruck Next Reaction method/LSODA method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/doi/10.1007/978-1-59745-525-1_2" xsd:anyURI {comment="Pedro Mendes, Stefan Hoops, Sven Sahle, Ralph Gauges, Joseph Dada & Ursula Kummer. Computational modeling of biochemical networks using COPASI. Methods in Molecular Biology 500, 17–59 (2009)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1016/j.jbiotec.2017.06.1200" xsd:anyURI {comment="Frank T. Bergmann, Stefan Hoops, Brian Klahn, Ursula Kummer, Pedro Mendes Jürgen Pahle & Sven Sahle. COPASI and its applications in biotechnology. Journal of Biotechnology 261, 215–220 (2017)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1093/bioinformatics/btl485" xsd:anyURI {comment="Stefan Hoops, Sven Sahle, Ralph Gauges, Christine Lee, Jürgen Pahle, Natalia Simus, Mudita Singhal, Liang Xu, Pedro Mendes & Ursula Kummer. COPASI—a complex pathway simulator. Bioinformatics 22 (24), 3067–3074 (2006)."}
 property_value: seeAlso "http://identifiers.org/doi/10.5555/1218112.1218421" xsd:anyURI {comment="Sven Sahle, Ralph Gauges, Jürgen Pahle, Natalia Simus, Ursula Kummer, Stefan Hoops, Christine Lee, Mudita Singhal, Liang Xu & Pedro Mendes. Simulation of biochemical networks using COPASI—a complex pathway simulator. Proceedings of the 2006 Winter Simulation Conference, Monterey, CA, USA, 1698–1706 (2006)."}
+property_value: skos:definition "Combines a deterministic numerical integration of ODEs with a stochastic simulation algorithm. The whole biochemical network is partitioned into a deterministic and a stochastic subnet internally. The deterministic subnet contains all reactions in which only species with high particle numbers take part. All reactions with at least one low-numbered species are in the stochastic subnet. The partitioning of the biochemical network can change dynamically during the simulation. The reaction probabilities of the stochastic subnet are approximated as constant during one stochastic step. A 4th-order Runge-Kutta method is used to numerically integrate the deterministic part of the system. The stochastic subnet is simulated by the Gibson-Bruck Next Reaction Method." xsd:string
 
 [Term]
-id: KISAO_0000562
+id: kisao:KISAO_0000562
 name: Pahle hybrid Gibson-Bruck Next Reaction method/LSODA method
-is_a: KISAO_0000231 ! Pahle hybrid method
-property_value: definition "Combines a deterministic numerical integration of ODEs with a stochastic simulation algorithm. The whole biochemical network is partitioned into a deterministic and a stochastic subnet internally. The deterministic subnet contains all reactions in which only species with high particle numbers take part. All reactions with at least one low-numbered species are in the stochastic subnet. The partitioning of the biochemical network can change dynamically during the simulation. The reaction probabilities of the stochastic subnet are approximated as constant during one stochastic step. The deterministic subnet is integrated with LSODA. The stochastic subnet is simulated by the Gibson-Bruck Next Reaction Method." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000231 ! Pahle hybrid method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/doi/10.1007/978-1-59745-525-1_2" xsd:anyURI {comment="Pedro Mendes, Stefan Hoops, Sven Sahle, Ralph Gauges, Joseph Dada & Ursula Kummer. Computational modeling of biochemical networks using COPASI. Methods in Molecular Biology 500, 17–59 (2009)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1016/j.jbiotec.2017.06.1200" xsd:anyURI {comment="Frank T. Bergmann, Stefan Hoops, Brian Klahn, Ursula Kummer, Pedro Mendes Jürgen Pahle & Sven Sahle. COPASI and its applications in biotechnology. Journal of Biotechnology 261, 215–220 (2017)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1093/bioinformatics/btl485" xsd:anyURI {comment="Stefan Hoops, Sven Sahle, Ralph Gauges, Christine Lee, Jürgen Pahle, Natalia Simus, Mudita Singhal, Liang Xu, Pedro Mendes & Ursula Kummer. COPASI—a complex pathway simulator. Bioinformatics 22 (24), 3067–3074 (2006)."}
 property_value: seeAlso "http://identifiers.org/doi/10.5555/1218112.1218421" xsd:anyURI {comment="Sven Sahle, Ralph Gauges, Jürgen Pahle, Natalia Simus, Ursula Kummer, Stefan Hoops, Christine Lee, Mudita Singhal, Liang Xu & Pedro Mendes. Simulation of biochemical networks using COPASI—a complex pathway simulator. Proceedings of the 2006 Winter Simulation Conference, Monterey, CA, USA, 1698–1706 (2006)."}
+property_value: skos:definition "Combines a deterministic numerical integration of ODEs with a stochastic simulation algorithm. The whole biochemical network is partitioned into a deterministic and a stochastic subnet internally. The deterministic subnet contains all reactions in which only species with high particle numbers take part. All reactions with at least one low-numbered species are in the stochastic subnet. The partitioning of the biochemical network can change dynamically during the simulation. The reaction probabilities of the stochastic subnet are approximated as constant during one stochastic step. The deterministic subnet is integrated with LSODA. The stochastic subnet is simulated by the Gibson-Bruck Next Reaction Method." xsd:string
 
 [Term]
-id: KISAO_0000563
+id: kisao:KISAO_0000563
 name: Pahle hybrid Gibson-Bruck Next Reaction method/RK-45 method
-is_a: KISAO_0000231 ! Pahle hybrid method
-property_value: definition "Combines a deterministic numerical integration of ODEs with a stochastic simulation algorithm. The whole biochemical network is partitioned into a deterministic and a stochastic subnet internally. The deterministic subnet contains all reactions in which only species with high particle numbers take part. All reactions with at least one low-numbered species are in the stochastic subnet. The partitioning of the biochemical network can change dynamically during the simulation. The reaction probabilities of the stochastic subnet are approximated as constant during one stochastic step. The deterministic subnet is integrated with RK-45. The stochastic subnet is simulated by the Gibson-Bruck Next Reaction Method." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000231 ! Pahle hybrid method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/doi/10.1007/978-1-59745-525-1_2" xsd:anyURI {comment="Pedro Mendes, Stefan Hoops, Sven Sahle, Ralph Gauges, Joseph Dada & Ursula Kummer. Computational modeling of biochemical networks using COPASI. Methods in Molecular Biology 500, 17–59 (2009)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1016/j.jbiotec.2017.06.1200" xsd:anyURI {comment="Frank T. Bergmann, Stefan Hoops, Brian Klahn, Ursula Kummer, Pedro Mendes Jürgen Pahle & Sven Sahle. COPASI and its applications in biotechnology. Journal of Biotechnology 261, 215–220 (2017)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1093/bioinformatics/btl485" xsd:anyURI {comment="Stefan Hoops, Sven Sahle, Ralph Gauges, Christine Lee, Jürgen Pahle, Natalia Simus, Mudita Singhal, Liang Xu, Pedro Mendes & Ursula Kummer. COPASI—a complex pathway simulator. Bioinformatics 22 (24), 3067–3074 (2006)."}
 property_value: seeAlso "http://identifiers.org/doi/10.5555/1218112.1218421" xsd:anyURI {comment="Sven Sahle, Ralph Gauges, Jürgen Pahle, Natalia Simus, Ursula Kummer, Stefan Hoops, Christine Lee, Mudita Singhal, Liang Xu & Pedro Mendes. Simulation of biochemical networks using COPASI—a complex pathway simulator. Proceedings of the 2006 Winter Simulation Conference, Monterey, CA, USA, 1698–1706 (2006)."}
+property_value: skos:definition "Combines a deterministic numerical integration of ODEs with a stochastic simulation algorithm. The whole biochemical network is partitioned into a deterministic and a stochastic subnet internally. The deterministic subnet contains all reactions in which only species with high particle numbers take part. All reactions with at least one low-numbered species are in the stochastic subnet. The partitioning of the biochemical network can change dynamically during the simulation. The reaction probabilities of the stochastic subnet are approximated as constant during one stochastic step. The deterministic subnet is integrated with RK-45. The stochastic subnet is simulated by the Gibson-Bruck Next Reaction Method." xsd:string
 
 [Term]
-id: KISAO_0000564
+id: kisao:KISAO_0000564
 name: stochastic Runge-Kutta method
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: definition "Technique for the approximate numerical solution of a systems of stochastic differential equations (SDEs). The method is a generalisation of the Runge-Kutta method for ordinary differential equations to stochastic differential equations." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+is_a: kisao:KISAO_0000697 ! SDE solver
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000483 ! step size
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000261 ! Euler method
+property_value: dc:creator "JRK" xsd:string
 property_value: seeAlso "https://en.wikipedia.org/wiki/Runge%E2%80%93Kutta_method_(SDE)" xsd:anyURI
+property_value: skos:definition "Technique for the approximate numerical solution of a systems of stochastic differential equations (SDEs). The method is a generalisation of the Runge-Kutta method for ordinary differential equations to stochastic differential equations." xsd:string
+
+[Term]
+id: kisao:KISAO_0000565
+name: absolute tolerance for root finding
+is_a: kisao:KISAO_0000211 ! absolute tolerance
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: skos:definition "Absolute error tolerance for root finding." xsd:string
 
 [Term]
-id: KISAO_0000566
+id: kisao:KISAO_0000566
 name: stochastic second order Runge-Kutta method
-is_a: KISAO_0000564 ! stochastic Runge-Kutta method
-property_value: altLabel "RI5" xsd:string {comment="EXACT"}
-property_value: definition "Technique for the second order approximate numerical solution of a systems of stochastic differential equations (SDEs). The method is a generalisation of the Runge-Kutta method for ordinary differential equations to stochastic differential equations." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+is_a: kisao:KISAO_0000564 ! stochastic Runge-Kutta method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000565 {maxCardinality="1"} ! absolute tolerance for root finding
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000567 {maxCardinality="1"} ! force physical correctness
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
 property_value: seeAlso "http://identifiers.org/doi/10.1137/060673308" xsd:anyURI {comment="Andreas Rößler. Second order Runge-Kutta methods for Itô stochastic differential equations. SIAM Journal Numerical Analysis 47 (3), 1713–1738 (2009)."}
+property_value: skos:altLabel "RI5" xsd:string {comment="EXACT"}
+property_value: skos:definition "Technique for the second order approximate numerical solution of a systems of stochastic differential equations (SDEs). The method is a generalisation of the Runge-Kutta method for ordinary differential equations to stochastic differential equations." xsd:string
 
 [Term]
-id: KISAO_0000568
+id: kisao:KISAO_0000567
+name: force physical correctness
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: skos:definition "Indicates whether to force physical correctness." xsd:string
+
+[Term]
+id: kisao:KISAO_0000568
 name: NLEQ1
-is_a: KISAO_0000408 ! Newton-type method
-property_value: altLabel "Newton-type method for solveing non-linear (NL) equations (EQ)" xsd:string
-property_value: altLabel "numerical solution of nonlinear (NL) equations (EQ) especially designed for numerically sensitive problems" xsd:string
-property_value: definition "Damped Newton-algorithm with rank strategy for systems of highly nonlinear equations.\n\nGlobal Newton method with error oriented convergence criterion; arbitrary selection of direct linear equation solver." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+is_a: kisao:KISAO_0000408 ! Newton-type method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
 property_value: seeAlso "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.3751" xsd:anyURI {comment="Ulrich Nowak & Lutz Weimann. A family of Newton codes for systems of highly nonlinear equations - algorithm, implementation, application. Konrad-Zuse-Zentrum für Informationstechnik Berlin 91-10 (1991)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1007/978-3-642-23899-4" xsd:anyURI {comment="Peter Deuflhard. Newton methods for nonlinear problems. Affine Invariance and Adaptive Algorithms (2004)."}
+property_value: skos:altLabel "Newton-type method for solveing non-linear (NL) equations (EQ)" xsd:string
+property_value: skos:altLabel "numerical solution of nonlinear (NL) equations (EQ) especially designed for numerically sensitive problems" xsd:string
+property_value: skos:definition "Damped Newton-algorithm with rank strategy for systems of highly nonlinear equations.\n\nGlobal Newton method with error oriented convergence criterion; arbitrary selection of direct linear equation solver." xsd:string
 
 [Term]
-id: KISAO_0000569
+id: kisao:KISAO_0000569
 name: NLEQ2
-is_a: KISAO_0000408 ! Newton-type method
-property_value: altLabel "Newton-type method for solveing non-linear (NL) equations (EQ)" xsd:string
-property_value: altLabel "numerical solution of nonlinear (NL) equations (EQ) especially designed for numerically sensitive problems" xsd:string
-property_value: definition "Damped Newton-algorithm with rank strategy for systems of highly nonlinear equations.\n\nGlobal Newton method with error oriented convergence criterion; QR-decomposition with subcondition number estimate." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+is_a: kisao:KISAO_0000408 ! Newton-type method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
 property_value: seeAlso "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.3751" xsd:anyURI {comment="Ulrich Nowak & Lutz Weimann. A family of Newton codes for systems of highly nonlinear equations - algorithm, implementation, application. Konrad-Zuse-Zentrum für Informationstechnik Berlin 91-10 (1991)."}
 property_value: seeAlso "http://identifiers.org/doi/10.1007/978-3-642-23899-4" xsd:anyURI {comment="Peter Deuflhard. Newton methods for nonlinear problems. Affine Invariance and Adaptive Algorithms (2004)."}
+property_value: skos:altLabel "Newton-type method for solveing non-linear (NL) equations (EQ)" xsd:string
+property_value: skos:altLabel "numerical solution of nonlinear (NL) equations (EQ) especially designed for numerically sensitive problems" xsd:string
+property_value: skos:definition "Damped Newton-algorithm with rank strategy for systems of highly nonlinear equations.\n\nGlobal Newton method with error oriented convergence criterion; QR-decomposition with subcondition number estimate." xsd:string
+
+[Term]
+id: kisao:KISAO_0000570
+name: auto reduce tolerances
+is_a: kisao:KISAO_0000242 ! error control parameter
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/pysces" xsd:anyURI {comment="PySCeS"}
+property_value: skos:definition "Whether to automatically reduce tolerances." xsd:string
+
+[Term]
+id: kisao:KISAO_0000571
+name: absolute tolerance adjustment factor
+is_a: kisao:KISAO_0000597 ! tolerance
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/pysces" xsd:anyURI {comment="PySCeS"}
+property_value: skos:definition "How much to adjust the absolute tolerance." xsd:string
 
 [Term]
-id: KISAO_0000573
+id: kisao:KISAO_0000572
+name: level of superimposed noise
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/boolnet" xsd:anyURI {comment="BoolNet"}
+property_value: skos:altLabel "noise level" xsd:string {comment="EXACT"}
+property_value: skos:definition "Standard deviation of the Gaussian noise which is added to each prediction." xsd:string
+
+[Term]
+id: kisao:KISAO_0000573
 name: probabilistic logical model simulation method
-is_a: KISAO_0000319 ! Monte Carlo method
-is_a: KISAO_0000448 ! logical model simulation method
-property_value: definition "Qualitative (logical) models specify the evolution rules of their components. Probabilistic networks allow for specifying more than one transition function per variable/gene. Each of these functions has a probability to be chosen, where the probabilities of all functions for one variable sum up to 1. Transitions are performed synchronously by choosing one transition function for each gene according to their probabilities and applying them to the current state." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/boolnet" xsd:anyURI {comment="BoolNet"}
+is_a: kisao:KISAO_0000319 ! Monte Carlo method
+is_a: kisao:KISAO_0000448 ! logical model simulation method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000104 ! stochastic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000452 ! random updating policy
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/boolnet" xsd:anyURI {comment="BoolNet"}
 property_value: seeAlso "http://identifiers.org/doi/10.1093/bioinformatics/btq124" xsd:anyURI
+property_value: skos:definition "Qualitative (logical) models specify the evolution rules of their components. Probabilistic networks allow for specifying more than one transition function per variable/gene. Each of these functions has a probability to be chosen, where the probabilities of all functions for one variable sum up to 1. Transitions are performed synchronously by choosing one transition function for each gene according to their probabilities and applying them to the current state." xsd:string
+
+[Term]
+id: kisao:KISAO_0000574
+name: species transition probabilities
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/boolnet" xsd:anyURI {comment="BoolNet"}
+property_value: skos:definition "Probability of each species to be chosen for the next state transition." xsd:string
 
 [Term]
-id: KISAO_0000575
+id: kisao:KISAO_0000575
 name: hybrid tau-leaping method
-is_a: KISAO_0000039 ! tau-leaping method
-is_a: KISAO_0000352 ! hybrid method
-property_value: definition "A continuously coupled hybrid deterministic/stochastic simulation algorithm for biochemical networks. Biochemical species are classified as continuous, discrete, or switch. Tau-leaping is used to simulate stochastic species, and LSODA or another ODE integration method is used to simulate continuous species. Switch species are dynamically classified as either continuous or discrete at each timestep depending on a user defined error tolerance." xsd:string
-property_value: http://purl.org/dc/terms/creator "BD" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
+is_a: kisao:KISAO_0000039 ! tau-leaping method
+is_a: kisao:KISAO_0000352 ! hybrid method
+property_value: dc:creator "BD" xsd:string
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
 property_value: seeAlso "https://github.com/StochSS/GillesPy2" xsd:anyURI {comment="Drawert B et al. GillesPy2"}
+property_value: skos:definition "A continuously coupled hybrid deterministic/stochastic simulation algorithm for biochemical networks. Biochemical species are classified as continuous, discrete, or switch. Tau-leaping is used to simulate stochastic species, and LSODA or another ODE integration method is used to simulate continuous species. Switch species are dynamically classified as either continuous or discrete at each timestep depending on a user defined error tolerance." xsd:string
 
 [Term]
-id: KISAO_0000576
+id: kisao:KISAO_0000576
 name: quadratic MOMA
-is_a: KISAO_0000593 ! MOMA
-disjoint_from: KISAO_0000579 ! linear MOMA
-property_value: altLabel "minimization of metabolic adjustment" xsd:string
-property_value: altLabel "MOMA" xsd:string
-property_value: altLabel "Quadratic Minimization of Metabolic Adjustment" xsd:string {comment="EXACT"}
-property_value: altLabel "quadratic minimization of metabolic adjustment" xsd:string
-property_value: definition "Minimization of metabolic adjustment (MOMA) is an extension of FBA for the prediction of flux distributions in gene knockouts. MOMA employs quadratic programming to identify the closest point (in terms of its Euclidean distance) in the permissible flux space of the knockout to the wild-type flux vector by solving the optimization problem\n\nMin sum((fluxAi - fluxBi)^2) + sum(fluxAi)^(fluxMinimizationWeight) + sum(fluxBi)^(fluxMinimizationWeight)" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/optflux" xsd:anyURI {comment="Optflux"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/raven" xsd:anyURI {comment="RAVEN"}
+is_a: kisao:KISAO_0000593 ! MOMA
+disjoint_from: kisao:KISAO_0000579 ! linear MOMA
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000577 ! flux minimization weight
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/optflux" xsd:anyURI {comment="Optflux"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/raven" xsd:anyURI {comment="RAVEN"}
 property_value: seeAlso "http://identifiers.org/doi/10.1073/pnas.232349399" xsd:anyURI {comment="Segre, D., Vitkup, D., & Church, G. M. (2002). Analysis of optimality in natural and perturbed metabolic networks. Proceedings of the National Academy of Sciences, 99(23), 15112-15117."}
+property_value: skos:altLabel "minimization of metabolic adjustment" xsd:string
+property_value: skos:altLabel "MOMA" xsd:string
+property_value: skos:altLabel "Quadratic Minimization of Metabolic Adjustment" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "quadratic minimization of metabolic adjustment" xsd:string
+property_value: skos:definition "Minimization of metabolic adjustment (MOMA) is an extension of FBA for the prediction of flux distributions in gene knockouts. MOMA employs quadratic programming to identify the closest point (in terms of its Euclidean distance) in the permissible flux space of the knockout to the wild-type flux vector by solving the optimization problem\n\nMin sum((fluxAi - fluxBi)^2) + sum(fluxAi)^(fluxMinimizationWeight) + sum(fluxBi)^(fluxMinimizationWeight)" xsd:string
+
+[Term]
+id: kisao:KISAO_0000577
+name: flux minimization weight
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "The degree to which minimization of the sum of fluxes should be taken into account in Minimization of Metabolic Adjustment (MOMA) which solvers the optimization problem\n \nMin sum((fluxAi - fluxBi)^2) + sum(fluxAi)^(fluxMinimizationWeight) + sum(fluxBi)^(fluxMinimizationWeight)" xsd:string
 
 [Term]
-id: KISAO_0000579
+id: kisao:KISAO_0000578
+name: nested algorithm
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:altLabel "nested method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "subalgorithm" xsd:string {comment="EXACT"}
+property_value: skos:definition "A nested algorithm of an algorithm" xsd:string
+
+[Term]
+id: kisao:KISAO_0000579
 name: linear MOMA
-is_a: KISAO_0000593 ! MOMA
-property_value: altLabel "Linear Minimization of Metabolic Adjustment" xsd:string {comment="EXACT"}
-property_value: altLabel "linear minimization of metabolic adjustment" xsd:string
-property_value: definition "Linear minimization of metabolic adjustment (MOMA) is an extension of FBA for the prediction of flux distributions in gene knockouts. Linear MOMA employs linear programming to identify the closest point (in terms of its L1 norm) in the permissible flux space of the knockout to the wild-type flux vector by solving the optimization problem\n\nMin sum(|fluxAi - fluxBi|)" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/optflux" xsd:anyURI {comment="Optflux"}
+is_a: kisao:KISAO_0000593 ! MOMA
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/optflux" xsd:anyURI {comment="Optflux"}
 property_value: seeAlso "http://identifiers.org/doi/10.1038/ng.846" xsd:anyURI {comment="Szappanos, B., Kovács, K., Szamecz, B., Honti, F., Costanzo, M., Baryshnikova, A., ... & Andrews, B. J. (2011). An integrated approach to characterize genetic interaction networks in yeast metabolism. Nature genetics, 43(7), 656-662."}
+property_value: skos:altLabel "Linear Minimization of Metabolic Adjustment" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "linear minimization of metabolic adjustment" xsd:string
+property_value: skos:definition "Linear minimization of metabolic adjustment (MOMA) is an extension of FBA for the prediction of flux distributions in gene knockouts. Linear MOMA employs linear programming to identify the closest point (in terms of its L1 norm) in the permissible flux space of the knockout to the wild-type flux vector by solving the optimization problem\n\nMin sum(|fluxAi - fluxBi|)" xsd:string
 
 [Term]
-id: KISAO_0000580
+id: kisao:KISAO_0000580
 name: ROOM
-is_a: KISAO_0000407 ! steady state method
-is_a: KISAO_0000622 ! flux balance method
-property_value: altLabel "Regulatory on/off minimization of metabolic flux changes" xsd:string {comment="EXACT"}
-property_value: altLabel "regulatory on/off minimization of metabolic flux changes" xsd:string
-property_value: definition "Constraint-based algorithm for predicting the metabolic steady state after gene knockouts which aims to minimize the number of significant flux changes (hence on/off) with respect to the wild type." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/optflux" xsd:anyURI {comment="Optflux"}
+is_a: kisao:KISAO_0000622 ! flux balance method
+is_a: kisao:KISAO_0000630 ! general steady state method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/optflux" xsd:anyURI {comment="Optflux"}
 property_value: seeAlso "http://identifiers.org/doi/10.1073/pnas.0406346102" xsd:anyURI {comment="Shlomi, T., Berkman, O., & Ruppin, E. (2005). Regulatory on/off minimization of metabolic flux changes after genetic perturbations. Proceedings of the national academy of sciences, 102(21), 7695-7700."}
+property_value: skos:altLabel "Regulatory on/off minimization of metabolic flux changes" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "regulatory on/off minimization of metabolic flux changes" xsd:string
+property_value: skos:definition "Constraint-based algorithm for predicting the metabolic steady state after gene knockouts which aims to minimize the number of significant flux changes (hence on/off) with respect to the wild type." xsd:string
 
 [Term]
-id: KISAO_0000581
+id: kisao:KISAO_0000581
 name: BKMC
-is_a: KISAO_0000319 ! Monte Carlo method
-is_a: KISAO_0000573 ! probabilistic logical model simulation method
-relationship: KISAO_0000359 KISAO_0000029 ! Gillespie direct algorithm
-property_value: altLabel "Boolean Kinetic Monte-Carlo" xsd:string {comment="EXACT"}
-property_value: altLabel "Boolean kinetic Monte-Carlo" xsd:string
-property_value: definition "The Boolean kinetic Monte Carlo method (BKMC) is a natural generalization of the asynchronous Boolean simulation method, with a direct probabilistic interpretation. In the BKMC framework, the dynamics is parameterized by a biological time and the order of update is noisy, which is less strict than priority classes introduced in GINsin. A BKMC model is specified by logical rules as in regular Boolean models but with a more precise information: a numerical rate is added for each transition of each node." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/maboss" xsd:anyURI {comment="MaBoSS"}
+is_a: kisao:KISAO_0000319 ! Monte Carlo method
+is_a: kisao:KISAO_0000573 ! probabilistic logical model simulation method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000322 ! hybridity
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000452 ! random updating policy
+relationship: kisao:KISAO_0000359 kisao:KISAO_0000029 ! Gillespie direct algorithm
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/maboss" xsd:anyURI {comment="MaBoSS"}
 property_value: seeAlso "http://identifiers.org/doi/10.1186/1752-0509-6-116" xsd:anyURI {comment="Stoll, G., Viara, E., Barillot, E., & Calzone, L. (2012). Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm. BMC systems biology, 6(1), 1-18."}
+property_value: skos:altLabel "Boolean Kinetic Monte-Carlo" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Boolean kinetic Monte-Carlo" xsd:string
+property_value: skos:definition "The Boolean kinetic Monte Carlo method (BKMC) is a natural generalization of the asynchronous Boolean simulation method, with a direct probabilistic interpretation. In the BKMC framework, the dynamics is parameterized by a biological time and the order of update is noisy, which is less strict than priority classes introduced in GINsin. A BKMC model is specified by logical rules as in regular Boolean models but with a more precise information: a numerical rate is added for each transition of each node." xsd:string
 
 [Term]
-id: KISAO_0000582
+id: kisao:KISAO_0000582
 name: Spatiocyte method
-is_a: KISAO_0000056 ! Smoluchowski equation based method
-property_value: definition "Lattice-based stochastic particle simulation method for biochemical reaction and diffusion processes." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell 4"}
+is_a: kisao:KISAO_0000056 ! Smoluchowski equation based method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell 4"}
 property_value: seeAlso "http://identifiers.org/doi/10.1038/npre.2009.3845.1" xsd:anyURI {comment="Arjunan, S., & Tomita, M. (2009). A new multicompartmental reaction-diffusion modeling method links transient membrane attachment of E. coli MinE to E-ring formation. Nature Precedings, 1-1."}
+property_value: skos:definition "Lattice-based stochastic particle simulation method for biochemical reaction and diffusion processes." xsd:string
+
+[Term]
+id: kisao:KISAO_0000583
+name: minimum order
+is_a: kisao:KISAO_0000594 ! order
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: skos:definition "Minimum order of method." xsd:string
 
 [Term]
-id: KISAO_0000585
+id: kisao:KISAO_0000584
+name: initial order
+is_a: kisao:KISAO_0000594 ! order
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: skos:definition "Initial order of method." xsd:string
+
+[Term]
+id: kisao:KISAO_0000585
 name: TOMS731
-is_a: KISAO_0000369 ! partial differential equation discretization method
-property_value: definition "Moving-grid interface for systems of one-dimensional time-dependent partial differential equations." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+is_a: kisao:KISAO_0000369 ! partial differential equation discretization method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
 property_value: seeAlso "http://identifiers.org/doi/10.1145/178365.178391" xsd:anyURI {comment="Blom, J. G., & Zegeling, P. A. (1994). Algorithm 731: a moving-grid interface for systems of one-dimensional time-dependent partial differential equations. ACM Transactions on Mathematical Software (TOMS), 20(2), 194-214."}
+property_value: skos:definition "Moving-grid interface for systems of one-dimensional time-dependent partial differential equations." xsd:string
 
 [Term]
-id: KISAO_0000586
+id: kisao:KISAO_0000586
 name: Gibson-Bruck next reaction algorithm with indexed priority queue
-is_a: KISAO_0000027 ! Gibson-Bruck next reaction algorithm
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/sbscl" xsd:anyURI {comment="SBSCL"}
+is_a: kisao:KISAO_0000027 ! Gibson-Bruck next reaction algorithm
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/sbscl" xsd:anyURI {comment="SBSCL"}
 
 [Term]
-id: KISAO_0000587
+id: kisao:KISAO_0000587
 name: IMEX
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: altLabel "Implicit-Explicit Runge-Kutta method" xsd:string {comment="EXACT"}
-property_value: altLabel "implicit-explicit Runge-Kutta method" xsd:string
-property_value: definition "Method for solving stiff and imaginary ODE problems" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/biouml" xsd:anyURI {comment="BioUML"}
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/biouml" xsd:anyURI {comment="BioUML"}
+property_value: skos:altLabel "Implicit-Explicit Runge-Kutta method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "implicit-explicit Runge-Kutta method" xsd:string
+property_value: skos:definition "Method for solving stiff and imaginary ODE problems" xsd:string
 
 [Term]
-id: KISAO_0000588
+id: kisao:KISAO_0000588
 name: flux sampling
-is_a: KISAO_0000407 ! steady state method
-property_value: definition "Method for sampling fluxes from the null space of a flux balance analysis model" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000622 ! flux balance method
+is_a: kisao:KISAO_0000630 ! general steady state method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Method for sampling fluxes from the null space of a flux balance analysis model" xsd:string
 
 [Term]
-id: KISAO_0000589
+id: kisao:KISAO_0000589
 name: ACB flux sampling method
-is_a: KISAO_0000588 ! flux sampling
-disjoint_from: KISAO_0000590 ! ACHR flux sampling method
-property_value: altLabel "Artificial centering boundary flux sampling method" xsd:string {comment="EXACT"}
-property_value: altLabel "artificial centering boundary flux sampling method" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+is_a: kisao:KISAO_0000588 ! flux sampling
+disjoint_from: kisao:KISAO_0000590 ! ACHR flux sampling method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
 property_value: seeAlso "http://identifiers.org/doi/10.1038/s41596-018-0098-2" xsd:anyURI {comment="Heirendt, L., Arreckx, S., Pfau, T., Mendoza, S. N., Richelle, A., Heinken, A., ... & Magnusdóttir, S. (2019). Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v. 3.0. Nature protocols, 14(3), 639-702."}
+property_value: skos:altLabel "Artificial centering boundary flux sampling method" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "artificial centering boundary flux sampling method" xsd:string
 
 [Term]
-id: KISAO_0000590
+id: kisao:KISAO_0000590
 name: ACHR flux sampling method
-is_a: KISAO_0000588 ! flux sampling
-property_value: altLabel "artificial centering hit-and-run flux sampling method" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/cobrapy" xsd:anyURI {comment="COBRApy"}
-property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+is_a: kisao:KISAO_0000588 ! flux sampling
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cobrapy" xsd:anyURI {comment="COBRApy"}
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
 property_value: seeAlso "http://identifiers.org/doi/10.1287/opre.46.1.84" xsd:anyURI {comment="Kaufman, D. E., & Smith, R. L. (1998). Direction choice for accelerated convergence in hit-and-run sampling. Operations Research, 46(1), 84-95."}
+property_value: skos:altLabel "artificial centering hit-and-run flux sampling method" xsd:string
 
 [Term]
-id: KISAO_0000591
+id: kisao:KISAO_0000591
 name: mdFBA
-is_a: KISAO_0000437 ! flux balance analysis
-property_value: altLabel "metabolic dilution flux balance analysis" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+is_a: kisao:KISAO_0000437 ! flux balance analysis
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
 property_value: seeAlso "http://identifiers.org/doi/10.1186/gb-2010-11-4-r43" xsd:anyURI {comment="Benyamini, T., Folger, O., Ruppin, E., & Shlomi, T. (2010). Flux balance analysis accounting for metabolite dilution. Genome biology, 11(4), R43."}
+property_value: skos:altLabel "metabolic dilution flux balance analysis" xsd:string
 
 [Term]
-id: KISAO_0000592
+id: kisao:KISAO_0000592
 name: dynamic rFBA
-is_a: KISAO_0000595 ! rFBA
-disjoint_from: KISAO_0000596 ! srFBA
-property_value: altLabel "dynamic regulatory flux balance analysis" xsd:string {comment="EXACT"}
-property_value: altLabel "regulatory flux balance analysis" xsd:string
-property_value: altLabel "rFBA" xsd:string
-property_value: definition "Method for predicting the dynamics of metabolic fluxes under patterns of the regulation of gene expression" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+is_a: kisao:KISAO_0000595 ! rFBA
+disjoint_from: kisao:KISAO_0000596 ! srFBA
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
 property_value: seeAlso "http://identifiers.org/doi/10.1006/jtbi.2001.2405" xsd:string {comment="Covert, M. W., Schilling, C. H., & Palsson, B. (2001). Regulation of gene expression in flux balance models of metabolism. Journal of theoretical biology, 213(1), 73-88."}
+property_value: skos:altLabel "dynamic regulatory flux balance analysis" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "regulatory flux balance analysis" xsd:string
+property_value: skos:altLabel "rFBA" xsd:string
+property_value: skos:definition "Method for predicting the dynamics of metabolic fluxes under patterns of the regulation of gene expression" xsd:string
 
 [Term]
-id: KISAO_0000593
+id: kisao:KISAO_0000593
 name: MOMA
-is_a: KISAO_0000407 ! steady state method
-is_a: KISAO_0000622 ! flux balance method
-property_value: altLabel "Minimization of Metabolic Adjustment" xsd:string {comment="EXACT"}
-property_value: altLabel "minimization of metabolic adjustment" xsd:string
-property_value: definition "minimization of metabolic adjustment (MOMA) is an extension of FBA for the prediction of flux distributions in gene knockouts. MOMA identifies the closest point in the permissible flux space of the knockout to the wild-type flux vector by solving an optimization problem." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000622 ! flux balance method
+is_a: kisao:KISAO_0000630 ! general steady state method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:altLabel "Minimization of Metabolic Adjustment" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "minimization of metabolic adjustment" xsd:string
+property_value: skos:definition "minimization of metabolic adjustment (MOMA) is an extension of FBA for the prediction of flux distributions in gene knockouts. MOMA identifies the closest point in the permissible flux space of the knockout to the wild-type flux vector by solving an optimization problem." xsd:string
 
 [Term]
-id: KISAO_0000595
+id: kisao:KISAO_0000594
+name: order
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Order of method" xsd:string
+
+[Term]
+id: kisao:KISAO_0000595
 name: rFBA
-is_a: KISAO_0000352 ! hybrid method
-is_a: KISAO_0000622 ! flux balance method
-property_value: altLabel "regulatory flux balance analysis" xsd:string {comment="EXACT"}
-property_value: definition "Method for predicting metabolic fluxes under patterns of the regulation of gene expression" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000352 ! hybrid method
+is_a: kisao:KISAO_0000622 ! flux balance method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:altLabel "regulatory flux balance analysis" xsd:string {comment="EXACT"}
+property_value: skos:definition "Method for predicting metabolic fluxes under patterns of the regulation of gene expression" xsd:string
 
 [Term]
-id: KISAO_0000596
+id: kisao:KISAO_0000596
 name: srFBA
-is_a: KISAO_0000437 ! flux balance analysis
-is_a: KISAO_0000595 ! rFBA
-property_value: altLabel "SR-FBA" xsd:string {comment="EXACT"}
-property_value: altLabel "steady-state regulatory flux balance analysis" xsd:string
-property_value: definition "Method for predicting steady-state metabolic fluxes under patterns of the regulation of gene expression" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+is_a: kisao:KISAO_0000437 ! flux balance analysis
+is_a: kisao:KISAO_0000595 ! rFBA
+property_value: dc:creator "JRK" xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1038/msb4100141" xsd:string {comment="Shlomi, T., Eisenberg, Y., Sharan, R., & Ruppin, E. (2007). A genome‐scale computational study of the interplay between transcriptional regulation and metabolism. Molecular systems biology, 3(1), 101."}
+property_value: skos:altLabel "SR-FBA" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "steady-state regulatory flux balance analysis" xsd:string
+property_value: skos:definition "Method for predicting steady-state metabolic fluxes under patterns of the regulation of gene expression" xsd:string
+
+[Term]
+id: kisao:KISAO_0000597
+name: tolerance
+is_a: kisao:KISAO_0000242 ! error control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Numeric value specifying the desired tolerance the user wants to achieve. A smaller value means that the prediction is calculated more accurately." xsd:string
 
 [Term]
-id: KISAO_0000598
+id: kisao:KISAO_0000598
 name: hybrid Gibson - Milstein method
-is_a: KISAO_0000352 ! hybrid method
-property_value: definition "A hybrid stochastic method partitions the system into subsets of fast and slow reactions and approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the Gibson algorithm. Fixed time step Milstein is used for approximate numerical solution of CLE." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: http://purl.org/dc/terms/creator "MLB" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+is_a: kisao:KISAO_0000352 ! hybrid method
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "MLB" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
 property_value: seeAlso "http://identifiers.org/doi/10.1186/1471-2105-7-93" xsd:anyURI {comment="H.Salis, V. Sotiropoulos and Y. Kaznessis,'Multiscale Hy3S: Hybrid stochastic simulation for supercomputers', BMC Bioinformatics 7:93 (2006)."}
+property_value: skos:definition "A hybrid stochastic method partitions the system into subsets of fast and slow reactions and approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the Gibson algorithm. Fixed time step Milstein is used for approximate numerical solution of CLE." xsd:string
 
 [Term]
-id: KISAO_0000599
+id: kisao:KISAO_0000599
 name: hybrid Gibson - Euler-Maruyama method
-is_a: KISAO_0000352 ! hybrid method
-property_value: definition "A hybrid stochastic method partitions the system into subsets of fast and slow reactions and approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the Gibson algorithm. Fixed time step Milstein is used for approximate numerical solution of CLE." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: http://purl.org/dc/terms/creator "MLB" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+is_a: kisao:KISAO_0000352 ! hybrid method
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "MLB" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
 property_value: seeAlso "http://identifiers.org/doi/10.1186/1471-2105-7-93" xsd:anyURI {comment="H.Salis, V. Sotiropoulos and Y. Kaznessis,'Multiscale Hy3S: Hybrid stochastic simulation for supercomputers', BMC Bioinformatics 7:93 (2006)."}
+property_value: skos:definition "A hybrid stochastic method partitions the system into subsets of fast and slow reactions and approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the Gibson algorithm. Fixed time step Milstein is used for approximate numerical solution of CLE." xsd:string
 
 [Term]
-id: KISAO_0000600
+id: kisao:KISAO_0000600
 name: hybrid adaptive Gibson - Milstein method
-is_a: KISAO_0000352 ! hybrid method
-property_value: definition "A hybrid stochastic method partitions the system into subsets of fast and slow reactions and approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the Gibson algorithm. Fixed time step Milstein is used for approximate numerical solution of CLE." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: http://purl.org/dc/terms/creator "MLB" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+is_a: kisao:KISAO_0000352 ! hybrid method
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "MLB" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
 property_value: seeAlso "http://identifiers.org/doi/10.1186/1471-2105-7-93" xsd:anyURI {comment="H.Salis, V. Sotiropoulos and Y. Kaznessis,'Multiscale Hy3S: Hybrid stochastic simulation for supercomputers', BMC Bioinformatics 7:93 (2006)."}
-
-[Term]
-id: KISAO_0000606
+property_value: skos:definition "A hybrid stochastic method partitions the system into subsets of fast and slow reactions and approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the Gibson algorithm. Fixed time step Milstein is used for approximate numerical solution of CLE." xsd:string
+
+[Term]
+id: kisao:KISAO_0000601
+name: number of trials
+is_a: kisao:KISAO_0000244 ! granularity control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "MLB" xsd:string
+property_value: skos:altLabel "trials" xsd:string
+property_value: skos:definition "Number of multiple trials (e.g., of a scatter search method)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000602
+name: minimum species threshold for continuous approximation
+is_a: kisao:KISAO_0000244 ! granularity control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "MLB" xsd:string
+property_value: skos:altLabel "Epsilon" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "epsilon" xsd:string
+property_value: skos:definition "Minimum number of molecules of both reactant and product species required for approximation as a continuous Markov process." xsd:string
+
+[Term]
+id: kisao:KISAO_0000603
+name: minimum reaction rate for continuous approximation
+is_a: kisao:KISAO_0000244 ! granularity control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "MLB" xsd:string
+property_value: skos:altLabel "Lambda" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "lambda" xsd:string
+property_value: skos:definition "Minimum reaction rate required for approximation as a continuous Markov process." xsd:string
+
+[Term]
+id: kisao:KISAO_0000604
+name: MSR tolerance
+is_a: kisao:KISAO_0000209 ! relative tolerance
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "MLB" xsd:string
+property_value: skos:altLabel "Multiple slow reactions tolerance" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "multiple slow reactions tolerance" xsd:string
+property_value: skos:definition "Maximum allowed effect of executing multiple slow reactions per numerical integration of the SDEs." xsd:string
+
+[Term]
+id: kisao:KISAO_0000605
+name: SDE tolerance
+is_a: kisao:KISAO_0000209 ! relative tolerance
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "MLB" xsd:string
+property_value: skos:altLabel "Maximum allowed value of the drift and diffusion errors." xsd:string {comment="EXACT"}
+property_value: skos:altLabel "maximum allowed value of the drift and diffusion errors." xsd:string
+property_value: skos:definition "Stochastic differential equation tolerance" xsd:string
+
+[Term]
+id: kisao:KISAO_0000606
 name: hierarchical stochastic simulation algorithm
-is_a: KISAO_0000241 ! Gillespie-like method
-relationship: KISAO_0000361 KISAO_0000029 ! Gillespie direct algorithm
-property_value: altLabel "hSSA" xsd:string {comment="EXACT"}
-property_value: definition "Fast, memory-efficient method for stochastic simulation of hierarchically organized models, such as a model of a cellular population where each cell in the population is represented by the same species and reactions." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+is_a: kisao:KISAO_0000241 ! Gillespie-like method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
+relationship: kisao:KISAO_0000361 kisao:KISAO_0000029 ! Gillespie direct algorithm
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
 property_value: seeAlso "http://identifiers.org/doi/10.3389/fbioe.2014.00055" xsd:anyURI {comment="Watanabe, L. H., & Myers, C. J. (2014). Hierarchical stochastic simulation algorithm for SBML models of genetic circuits. Frontiers in bioengineering and biotechnology, 2, 55."}
+property_value: skos:altLabel "hSSA" xsd:string {comment="EXACT"}
+property_value: skos:definition "Fast, memory-efficient method for stochastic simulation of hierarchically organized models, such as a model of a cellular population where each cell in the population is represented by the same species and reactions." xsd:string
 
 [Term]
-id: KISAO_0000607
+id: kisao:KISAO_0000607
 name: hierarchical Fehlberg method
-is_a: KISAO_0000086 ! Fehlberg method
-property_value: altLabel "hierarchical ODE integration method" xsd:string
-property_value: altLabel "hierarchical ordinary differential equation integration method" xsd:string
-property_value: altLabel "hODE" xsd:string {comment="EXACT"}
-property_value: definition "Method for continuous simulation of hierarchically organized models, such as a model of a cellular population where each cell in the population is represented by the same species and reactions." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+is_a: kisao:KISAO_0000086 ! Fehlberg method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
 property_value: seeAlso "http://identifiers.org/doi/10.3389/fbioe.2014.00055" xsd:anyURI {comment="Watanabe, L. H., & Myers, C. J. (2014). Hierarchical stochastic simulation algorithm for SBML models of genetic circuits. Frontiers in bioengineering and biotechnology, 2, 55."}
+property_value: skos:altLabel "hierarchical ODE integration method" xsd:string
+property_value: skos:altLabel "hierarchical ordinary differential equation integration method" xsd:string
+property_value: skos:altLabel "hODE" xsd:string {comment="EXACT"}
+property_value: skos:definition "Method for continuous simulation of hierarchically organized models, such as a model of a cellular population where each cell in the population is represented by the same species and reactions." xsd:string
 
 [Term]
-id: KISAO_0000608
+id: kisao:KISAO_0000608
 name: hierarchical flux balance analysis
-is_a: KISAO_0000437 ! flux balance analysis
-property_value: altLabel "hFBA" xsd:string {comment="EXACT"}
-property_value: altLabel "Hierarchical FBA" xsd:string {comment="EXACT"}
-property_value: altLabel "hierarchical FBA" xsd:string
-property_value: definition "Method for constraint-based simulation of hierarchically organized models, such as a model of a cellular population where each cell in the population is represented by the same species and reactions." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+is_a: kisao:KISAO_0000437 ! flux balance analysis
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
 property_value: seeAlso "http://identifiers.org/doi/10.3389/fbioe.2014.00055" xsd:anyURI {comment="Watanabe, L. H., & Myers, C. J. (2014). Hierarchical stochastic simulation algorithm for SBML models of genetic circuits. Frontiers in bioengineering and biotechnology, 2, 55."}
+property_value: skos:altLabel "hFBA" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "Hierarchical FBA" xsd:string {comment="EXACT"}
+property_value: skos:altLabel "hierarchical FBA" xsd:string
+property_value: skos:definition "Method for constraint-based simulation of hierarchically organized models, such as a model of a cellular population where each cell in the population is represented by the same species and reactions." xsd:string
 
 [Term]
-id: KISAO_0000609
+id: kisao:KISAO_0000609
 name: embedded Runge-Kutta Prince-Dormand (8,9) method
-is_a: KISAO_0000302 ! embedded Runge-Kutta method
-property_value: altLabel "RK8PD" xsd:string {comment="EXACT"}
-property_value: definition "An embedded Runge-Kutta integrator of order 8(9)." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+is_a: kisao:KISAO_0000302 ! embedded Runge-Kutta method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: skos:altLabel "RK8PD" xsd:string {comment="EXACT"}
+property_value: skos:definition "An embedded Runge-Kutta integrator of order 8(9)." xsd:string
 
 [Term]
-id: KISAO_0000610
+id: kisao:KISAO_0000610
 name: composite-rejection stochastic simulation algorithm
-is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
-property_value: altLabel "SSA-CR" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+is_a: kisao:KISAO_0000333 ! accelerated stochastic simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000236 ! exact solution
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
 property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2919546" xsd:anyURI {comment="Slepoy, A., Thompson, A. P., & Plimpton, S. J. (2008). A constant-time kinetic Monte Carlo algorithm for simulation of large biochemical reaction networks. The journal of chemical physics, 128(20), 05B618."}
+property_value: skos:altLabel "SSA-CR" xsd:string
 
 [Term]
-id: KISAO_0000611
+id: kisao:KISAO_0000611
 name: incremental stochastic simulation algorithm
-is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
-property_value: altLabel "iSSA" xsd:string {comment="EXACT"}
-property_value: definition "Performs local averaging over small time-intervals to compute statistics on typical behavior." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "https://identifers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+is_a: kisao:KISAO_0000335 ! generalized stochastic simulation algorithm
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "https://identifers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
 property_value: seeAlso "http://identifiers.org/doi/10.1109/ISCAS.2010.5537539" xsd:anyURI {comment="Winstead, C., Madsen, C., & Myers, C. (2010, May). iSSA: An incremental stochastic simulation algorithm for genetic circuits. In Proceedings of 2010 IEEE International Symposium on Circuits and Systems (pp. 553-556). IEEE."}
+property_value: skos:altLabel "iSSA" xsd:string {comment="EXACT"}
+property_value: skos:definition "Performs local averaging over small time-intervals to compute statistics on typical behavior." xsd:string
 
 [Term]
-id: KISAO_0000612
+id: kisao:KISAO_0000612
 name: implicit 4th order Runge-Kutta method at Gaussian points
-is_a: KISAO_0000064 ! Runge-Kutta based method
-property_value: altLabel "RK4IMP" xsd:string {comment="EXACT"}
-property_value: http://purl.org/dc/terms/created "2021-01-25" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:string {comment="iBioSim"}
+is_a: kisao:KISAO_0000064 ! Runge-Kutta based method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+property_value: dc:created "2021-01-25" xsd:string
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:string {comment="iBioSim"}
+property_value: skos:altLabel "RK4IMP" xsd:string {comment="EXACT"}
 
 [Term]
-id: KISAO_0000613
+id: kisao:KISAO_0000613
 name: stochastic simulation algorithm with normally-distributed next reaction times
-is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
-property_value: altLabel "NMC" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+is_a: kisao:KISAO_0000335 ! generalized stochastic simulation algorithm
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: skos:altLabel "NMC" xsd:string
 
 [Term]
-id: KISAO_0000615
+id: kisao:KISAO_0000614
+name: implementation
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "An implementation of an algorithm. For example, simulation tools can this parameter to differentiate among C, Python, and Java implementations of the same algorithms and allow investigators to select one of these specific implementations through SED-ML." xsd:string
+
+[Term]
+id: kisao:KISAO_0000615
 name: fully-implicit regular grid finite volume method with a variable time step
-is_a: KISAO_0000285 ! finite volume method
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+is_a: kisao:KISAO_0000285 ! finite volume method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
 
 [Term]
-id: KISAO_0000616
+id: kisao:KISAO_0000616
 name: semi-implicit regular grid finite volume method with a fixed time step
-is_a: KISAO_0000285 ! finite volume method
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+is_a: kisao:KISAO_0000285 ! finite volume method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
 
 [Term]
-id: KISAO_0000617
+id: kisao:KISAO_0000617
 name: IDA-CVODE hybrid method
-is_a: KISAO_0000352 ! hybrid method
-property_value: definition "Meta algorithm which chooses between IDA and CVODE depending on the problem to be solved.\n\nCVODE is used for ordinary differential equation (ODE) systems. IDA is used for differential-algebraic equation (DAE) systems." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+is_a: kisao:KISAO_0000352 ! hybrid method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: skos:definition "Meta algorithm which chooses between IDA and CVODE depending on the problem to be solved.\n\nCVODE is used for ordinary differential equation (ODE) systems. IDA is used for differential-algebraic equation (DAE) systems." xsd:string
 
 [Term]
-id: KISAO_0000618
+id: kisao:KISAO_0000618
 name: bunker
-is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
-property_value: definition "A variant of the stochastic simulation algorithm (SSA) in which the time to the next reaction is equated to the mean inter-event time (inverse of the sum of the propensitites of the reactions) rather than sampled from a distribution parameterized by this mean inter-event time. In this method, the next reaction time is deterministic rather than stochastic as in SSA." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+is_a: kisao:KISAO_0000335 ! generalized stochastic simulation algorithm
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: skos:definition "A variant of the stochastic simulation algorithm (SSA) in which the time to the next reaction is equated to the mean inter-event time (inverse of the sum of the propensitites of the reactions) rather than sampled from a distribution parameterized by this mean inter-event time. In this method, the next reaction time is deterministic rather than stochastic as in SSA." xsd:string
 
 [Term]
-id: KISAO_0000619
+id: kisao:KISAO_0000619
 name: emc-sim
-is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
-property_value: definition "A variant of the stochastic simulation algorithm (SSA) in which the time to the next reaction is a constant equal to 1 time unit. In this method, the next reaction time is deterministic rather than stochastic as in SSA." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+is_a: kisao:KISAO_0000335 ! generalized stochastic simulation algorithm
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: skos:definition "A variant of the stochastic simulation algorithm (SSA) in which the time to the next reaction is a constant equal to 1 time unit. In this method, the next reaction time is deterministic rather than stochastic as in SSA." xsd:string
 
 [Term]
-id: KISAO_0000620
+id: kisao:KISAO_0000620
 name: parsimonius flux balance analysis
-is_a: KISAO_0000437 ! flux balance analysis
-property_value: altLabel "pFBA" xsd:string
-property_value: definition "A technique for selecting a flux distribution which is parsimonious by some metric, such as a solution which has the minimal number of active fluxes or a solution which has the smallest sum of active fluxes." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000437 ! flux balance analysis
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:altLabel "pFBA" xsd:string
+property_value: skos:definition "A technique for selecting a flux distribution which is parsimonious by some metric, such as a solution which has the minimal number of active fluxes or a solution which has the smallest sum of active fluxes." xsd:string
 
 [Term]
-id: KISAO_0000621
+id: kisao:KISAO_0000621
 name: stochastic simulation leaping method
-is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000333 ! accelerated stochastic simulation algorithm
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
 
 [Term]
-id: KISAO_0000622
+id: kisao:KISAO_0000622
 name: flux balance method
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000685 ! biological state optimization method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000691 ! metabolic system
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+
+[Term]
+id: kisao:KISAO_0000623
+name: flux balance problem
+is_a: kisao:KISAO_0000370 ! type of problem
+property_value: dc:creator "JRK" xsd:string
 
 [Term]
-id: KISAO_0000624
+id: kisao:KISAO_0000624
 name: method for solving a system of linear equations
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: definition "method for solving a system of linear equations\n\nExample system of equations:\n\n3x + 2y - z = 0\n2x - 2y + 4z = 0\n-x + 1/2y - z = 0" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000376 ! linearity of equation
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "method for solving a system of linear equations\n\nExample system of equations:\n\n3x + 2y - z = 0\n2x - 2y + 4z = 0\n-x + 1/2y - z = 0" xsd:string
 
 [Term]
-id: KISAO_0000625
+id: kisao:KISAO_0000625
 name: dense direct solver
-is_a: KISAO_0000624 ! method for solving a system of linear equations
-property_value: altLabel "denese" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "CVODE" xsd:string
+is_a: kisao:KISAO_0000624 ! method for solving a system of linear equations
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "CVODE" xsd:string
+property_value: skos:altLabel "denese" xsd:string
 
 [Term]
-id: KISAO_0000626
+id: kisao:KISAO_0000626
 name: band direct solver
-is_a: KISAO_0000624 ! method for solving a system of linear equations
-property_value: altLabel "banded" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "CVODE" xsd:string
+is_a: kisao:KISAO_0000624 ! method for solving a system of linear equations
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "CVODE" xsd:string
+property_value: skos:altLabel "banded" xsd:string
 
 [Term]
-id: KISAO_0000627
+id: kisao:KISAO_0000627
 name: diagonal approximate Jacobian solver
-is_a: KISAO_0000624 ! method for solving a system of linear equations
-property_value: altLabel "diagonal" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "CVODE" xsd:string
+is_a: kisao:KISAO_0000624 ! method for solving a system of linear equations
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "CVODE" xsd:string
+property_value: skos:altLabel "diagonal" xsd:string
+
+[Term]
+id: kisao:KISAO_0000628
+name: modelling and simulation algorithm parameter value
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A value of a parameter of an algorithm" xsd:string
+
+[Term]
+id: kisao:KISAO_0000629
+name: null
+is_a: kisao:KISAO_0000628 ! modelling and simulation algorithm parameter value
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:altLabel "none" xsd:string
 
 [Term]
-id: KISAO_0000630
-name: root-finding method
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: definition "Method for finding the root of a function (f(x) = 0)." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+id: kisao:KISAO_0000630
+name: general steady state method
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:altLabel "root-finding method" xsd:string
+property_value: skos:definition "A method looking for a steady state of a dynamic system." xsd:string
 
 [Term]
-id: KISAO_0000631
+id: kisao:KISAO_0000631
 name: iterative root-finding method
-is_a: KISAO_0000630 ! root-finding method
-property_value: definition "Iterative method for finding the root of a function (f(x) = 0)." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000407 ! steady state root-finding method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Iterative method for finding the root of a function (f(x) = 0)." xsd:string
 
 [Term]
-id: KISAO_0000632
+id: kisao:KISAO_0000632
 name: functional iteration root-finding method
-is_a: KISAO_0000631 ! iterative root-finding method
-property_value: definition "Iterative method for finding the root of a function f(x) given by\n\ny^{n(m+1)} = h_{n} β_{n,0} f(t_{n}, y^{n(m)}) + a_n\n\nThis method only involves evaluations of f. This method is suitable for non-stiff functions." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "CVODE" xsd:string
+is_a: kisao:KISAO_0000631 ! iterative root-finding method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "CVODE" xsd:string
 property_value: seeAlso "https://bookdown.org/rdpeng/advstatcomp/functional-iteration.html" xsd:anyURI {comment="Roger Peng. Advanced Statistical Computing."}
+property_value: skos:definition "Iterative method for finding the root of a function f(x) given by\n\ny^{n(m+1)} = h_{n} β_{n,0} f(t_{n}, y^{n(m)}) + a_n\n\nThis method only involves evaluations of f. This method is suitable for non-stiff functions." xsd:string
+
+[Term]
+id: kisao:KISAO_0000633
+name: computational function
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A mathematical function such as the calculation of a minimum, maximum, or mean of a set of values." xsd:string
+
+[Term]
+id: kisao:KISAO_0000634
+name: scaled property
+is_a: kisao:KISAO_0000820 ! model and simulation property characteristic
+property_value: dc:created "JRK" xsd:string
+
+[Term]
+id: kisao:KISAO_0000635
+name: unscaled property
+is_a: kisao:KISAO_0000820 ! model and simulation property characteristic
+property_value: dc:creator "JRK" xsd:string
+
+[Term]
+id: kisao:KISAO_0000636
+name: primary property
+is_a: kisao:KISAO_0000820 ! model and simulation property characteristic
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "A primary output of a simulation." xsd:string
+
+[Term]
+id: kisao:KISAO_0000637
+name: derived property
+is_a: kisao:KISAO_0000820 ! model and simulation property characteristic
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "An output of a simulation which can be derived from its primary outputs." xsd:string
+
+[Term]
+id: kisao:KISAO_0000638
+name: level
+is_a: kisao:KISAO_0000831 ! model and simulation property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000822 ! extensive property
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "A level such as of a qualitative variable." xsd:string
+
+[Term]
+id: kisao:KISAO_0000639
+name: flux
+is_a: kisao:KISAO_0000831 ! model and simulation property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000655 ! rate
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "A rate through an volume such as of a reaction of a constraint-based models." xsd:string
+
+[Term]
+id: kisao:KISAO_0000640
+name: lower bound
+is_a: kisao:KISAO_0000641 ! bound
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "A lower bound on an estimate of a quantity." xsd:string
+
+[Term]
+id: kisao:KISAO_0000641
+name: bound
+is_a: kisao:KISAO_0000820 ! model and simulation property characteristic
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "An upper or lower bound on an estimate of a quantity." xsd:string
+
+[Term]
+id: kisao:KISAO_0000642
+name: minimum flux
+is_a: kisao:KISAO_0000639 ! flux
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000640 ! lower bound
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Minimum possible flux such as computed by flux variability analysis (FVA, KISAO_0000526)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000643
+name: upper bound
+is_a: kisao:KISAO_0000641 ! bound
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "An upper bound on an estimate of a quantity." xsd:string
+
+[Term]
+id: kisao:KISAO_0000644
+name: maximum flux
+is_a: kisao:KISAO_0000639 ! flux
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000643 ! upper bound
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Maximum possible flux such as computed by flux variability analysis (FVA, KISAO_0000526)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000645
+name: objective value
+is_a: kisao:KISAO_0000831 ! model and simulation property
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Value of an objective function such as of a constraint-based model." xsd:string
+
+[Term]
+id: kisao:KISAO_0000646
+name: propensity
+is_a: kisao:KISAO_0000831 ! model and simulation property
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Tendency of an event such as of the firing of a reaction in the stochastic simulation algorithm (SSA, KISAO_0000029)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000647
+name: derivative
+is_a: kisao:KISAO_0000820 ! model and simulation property characteristic
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000821 ! intensive property
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Rate of change of a variable with respect to another variable." xsd:string
 
 [Term]
-id: KISAO_0000657
+id: kisao:KISAO_0000648
+name: step
+is_a: kisao:KISAO_0000831 ! model and simulation property
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Iteration such as along a pseudo timecourse of a logical simulation." xsd:string
+
+[Term]
+id: kisao:KISAO_0000649
+name: shadow price
+is_a: kisao:KISAO_0000650 ! sensitivity
+property_value: dc:creator "JRK" xsd:string
+property_value: seeAlso "https://en.wikipedia.org/wiki/Shadow_price" xsd:anyURI
+property_value: skos:definition "Change, per infinitesimal unit of the constraint, in the optimal value of the objective function of an optimization problem obtained by relaxing the constraint." xsd:string
+
+[Term]
+id: kisao:KISAO_0000650
+name: sensitivity
+is_a: kisao:KISAO_0000831 ! model and simulation property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000647 ! derivative
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "The sensitivity of a variable to another variable, such as the derivative a variable with respect to another." xsd:string
+
+[Term]
+id: kisao:KISAO_0000651
+name: reduced costs
+is_a: kisao:KISAO_0000650 ! sensitivity
+property_value: dc:creator "JRK" xsd:string
+property_value: seeAlso "https://en.wikipedia.org/wiki/Reduced_cost" xsd:anyURI
+property_value: skos:definition "The amount by which an objective function coefficient would have to improve before it would be possible for a corresponding variable to assume a positive value in the optimal solution." xsd:string
+
+[Term]
+id: kisao:KISAO_0000652
+name: concentration rate
+is_a: kisao:KISAO_0000834 ! rate of change
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000821 ! intensive property
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Rate of a process relative to a volume, such as the rate of a reaction in molar^-1 s^-1." xsd:string
+
+[Term]
+id: kisao:KISAO_0000653
+name: particle number rate
+is_a: kisao:KISAO_0000834 ! rate of change
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000822 ! extensive property
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Rate of a process in extensive/absolute units such as mole reactions per second." xsd:string
+
+[Term]
+id: kisao:KISAO_0000654
+name: amount rate
+is_a: kisao:KISAO_0000834 ! rate of change
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000822 ! extensive property
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "rate of a process in extensive/absolute units such as reactions per second." xsd:string
+
+[Term]
+id: kisao:KISAO_0000655
+name: rate
+is_a: kisao:KISAO_0000820 ! model and simulation property characteristic
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Speed at which a process is occuring such as the temporal rate of a chemical reaction," xsd:string
+
+[Term]
+id: kisao:KISAO_0000656
+name: use adaptive time steps
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: skos:definition "Whether an algorithm should use adaptive or fixed time steps." xsd:string
+
+[Term]
+id: kisao:KISAO_0000657
 name: sequential logical simulation method
-is_a: KISAO_0000448 ! logical model simulation method
-property_value: definition "Qualitative (logical) models specify the evolution rules of their components. In the case of a sequential updating, nodes are updated sequentially in a pre-determined deterministic order." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+is_a: kisao:KISAO_0000448 ! logical model simulation method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000103 ! deterministic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000454 ! constant updating policy
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000493 ! synchronous updating policy
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Qualitative (logical) models specify the evolution rules of their components. In the case of a sequential updating, nodes are updated sequentially in a pre-determined deterministic order." xsd:string
 
 [Term]
-id: KISAO_0000658
+id: kisao:KISAO_0000658
 name: logical model analysis method
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: definition "A method for analyzing a logical model, such as finding its fixed points." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000105 ! discrete variable
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A method for analyzing a logical model, such as finding its fixed points." xsd:string
 
 [Term]
-id: KISAO_0000659
+id: kisao:KISAO_0000659
 name: Naldi MDD logical model stable state search method
-is_a: KISAO_0000660 ! logical model stable state search method
-property_value: altLabel "Naldi Multi-valued Decision Diagram stable state search method" xsd:string
-property_value: definition "Efficient method for determining the stable states of a regulatory graph using a Multi-valued Decision Diagram (MDD) representation of the logical functions." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+is_a: kisao:KISAO_0000660 ! logical model stable state search method
+property_value: dc:creator "JRK" xsd:string
 property_value: seeAlso "http://identifiers.org/doi:10.1007/978-3-540-75140-3_16" xsd:anyURI {comment="Aurélien Naldi, Denis Thieffry and Claudine Chaouiya. Decision Diagrams for the Representation and Analysis of Logical Models of Genetic Networks. Computational Methods in Systems Biology 2007, 4695."}
+property_value: skos:altLabel "Naldi Multi-valued Decision Diagram stable state search method" xsd:string
+property_value: skos:definition "Efficient method for determining the stable states of a regulatory graph using a Multi-valued Decision Diagram (MDD) representation of the logical functions." xsd:string
 
 [Term]
-id: KISAO_0000660
+id: kisao:KISAO_0000660
 name: logical model stable state search method
-is_a: KISAO_0000658 ! logical model analysis method
-property_value: definition "Method for determining the stable states of a regulatory graph." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000658 ! logical model analysis method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Method for determining the stable states of a regulatory graph." xsd:string
 
 [Term]
-id: KISAO_0000661
+id: kisao:KISAO_0000661
 name: logical model trap space identification method
-is_a: KISAO_0000658 ! logical model analysis method
-property_value: definition "Method for determining the trap spaces, or stable motifs or symbolic stable states, of a regulatory graph," xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isOrganizational "true" xsd:boolean
+is_a: kisao:KISAO_0000658 ! logical model analysis method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "Method for determining the trap spaces, or stable motifs or symbolic stable states, of a regulatory graph," xsd:string
 
 [Term]
-id: KISAO_0000662
+id: kisao:KISAO_0000662
 name: Klarner ASP logical model trap space identification method
-is_a: KISAO_0000661 ! logical model trap space identification method
-property_value: altLabel "Klarner Answer Set Programming logical model trap space identification method" xsd:string
-property_value: definition "Optimization-based method rooted in answer set programming (ASP) for computing the trap spaces of a regulatory graph." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+is_a: kisao:KISAO_0000661 ! logical model trap space identification method
+property_value: dc:creator "JRK" xsd:string
 property_value: seeAlso "http://identifiers.org/doi:10.1007/s11047-015-9520-7" xsd:anyURI {comment="Hannes Klarner, Alexander Bockmayr, and Heike Siebert. Computing maximal and minimal trap spaces of Boolean networks. Natural Computing 14.4 (2015): 535-544."}
+property_value: skos:altLabel "Klarner Answer Set Programming logical model trap space identification method" xsd:string
+property_value: skos:definition "Optimization-based method rooted in answer set programming (ASP) for computing the trap spaces of a regulatory graph." xsd:string
 
 [Term]
-id: KISAO_0000663
+id: kisao:KISAO_0000663
 name: BDD logical model trap space identification method
-is_a: KISAO_0000661 ! logical model trap space identification method
-property_value: altLabel "Binary Decision Diagram logical model trap space identification method" xsd:string
-property_value: definition "Method for determining the trap spaces of a regulatory graph using a Binary Decision Diagram (BDD)." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+is_a: kisao:KISAO_0000661 ! logical model trap space identification method
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:altLabel "Binary Decision Diagram logical model trap space identification method" xsd:string
+property_value: skos:definition "Method for determining the trap spaces of a regulatory graph using a Binary Decision Diagram (BDD)." xsd:string
 
 [Term]
-id: KISAO_0000664
+id: kisao:KISAO_0000664
 name: Second order backward implicit product Euler scheme
-is_a: KISAO_0000000 ! modelling and simulation algorithm
-property_value: defaultLanguage "Method for solving Volterra equations. Uses the trapezoidal rule." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/xpp" xsd:anyURI {comment="XPP"}
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/xpp" xsd:anyURI {comment="XPP"}
+property_value: protege:defaultLanguage "Method for solving Volterra equations. Uses the trapezoidal rule." xsd:string
 property_value: seeAlso "http://identifiers.org/doi:10.1093/comjnl/12.4.393" xsd:anyURI {comment="Peter Linz. Numerical methods for Volterra integral equations of the first kind. Computer Journal 12 (4): 393–397 (1969)."}
 property_value: seeAlso "https://doi.org/10.1137/1.9781611970852" xsd:anyURI {comment="Peter Linz. Analytical and Numerical Methods for Volterra Equations. 1985."}
 
 [Term]
-id: KISAO_0000668
+id: kisao:KISAO_0000665
+name: maximum number of iterations for root finding
+is_a: kisao:KISAO_0000242 ! error control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/xpp" xsd:anyURI {comment="XPP"}
+
+[Term]
+id: kisao:KISAO_0000666
+name: Jacobian epsilon
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+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/xpp" xsd:anyURI {comment="XPP"}
+
+[Term]
+id: kisao:KISAO_0000667
+name: memory size
+is_a: kisao:KISAO_0000242 ! error control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/xpp" xsd:anyURI {comment="XPP"}
+property_value: skos:definition "Maximum number of points to store in memory, such as in the second order backward implicit product Euler scheme." xsd:string
+
+[Term]
+id: kisao:KISAO_0000668
 name: Numerical Recipes in C \"stiff\" Rosenbrock method
-is_a: KISAO_0000033 ! Rosenbrock method
-property_value: altLabel "stiff" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/xpp" xsd:anyURI {comment="XPP"}
+is_a: kisao:KISAO_0000033 ! Rosenbrock method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/xpp" xsd:anyURI {comment="XPP"}
 property_value: seeAlso "https://dl.acm.org/doi/10.5555/148286" xsd:anyURI {comment="William H. Press, Saul A. Teukolsky, William T. Vetterling & Brian P. Flannery. Numerical Recipes in C. The Art of Scientific Computing, 2nd Edition, 1992. Chapter 16. Pages 739-741."}
 property_value: seeAlso "Implementation of the Kaps and Rentrop using the parameters recommended by Shampine and Watts." xsd:string
 property_value: seeAlso "Shampine, L.F., and Watts, H.A. 1977, in Mathematical Software III, J.R. Rice, ed. (New York: Academic Press), pp. 257–275; 1979, Applied Mathematics and Computation, vol. 5, pp. 93–121." xsd:string
+property_value: skos:altLabel "stiff" xsd:string
 
 [Term]
-id: KISAO_0000669
+id: kisao:KISAO_0000669
 name: Resource Balance Analysis
-is_a: KISAO_0000407 ! steady state method
-property_value: altLabel "RBA" xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/rbapy" xsd:anyURI {comment="RBApy"}
+is_a: kisao:KISAO_0000630 ! general steady state method
+is_a: kisao:KISAO_0000685 ! biological state optimization method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000692 ! cellular system
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/rbapy" xsd:anyURI {comment="RBApy"}
 property_value: seeAlso "https://doi.org/10.1016/j.automatica.2011.02.038" xsd:anyURI {comment="A. Goelzer, V. Fromion, G. Scorletti. Cell design in bacteria as a convex optimization problem. Automatica, 47(6):1210-1218 (2011)."}
+property_value: skos:altLabel "RBA" xsd:string
+
+[Term]
+id: kisao:KISAO_0000670
+name: use multiple steps
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: skos:definition "Whether to perform a multiple time step simulation." xsd:string
+
+[Term]
+id: kisao:KISAO_0000671
+name: use stiff method
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
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+property_value: skos:definition "Specifies whether the integrator attempts to solve stiff equations." xsd:string
 
 [Term]
-id: KISAO_0000672
+id: kisao:KISAO_0000672
 name: Numerical Recipes in C \"quality-controlled Runge-Kutta\" method
-is_a: KISAO_0000321 ! Cash-Karp method
-property_value: altLabel "rkqs" xsd:string
-property_value: definition "Cash-Karp method with step size adjustment." xsd:string
-property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
-property_value: isImplementedIn "http://identifiers.org/biosimulators/xpp" xsd:anyURI {comment="XPP"}
+is_a: kisao:KISAO_0000321 ! Cash-Karp method
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/xpp" xsd:anyURI {comment="XPP"}
 property_value: seeAlso "https://dl.acm.org/doi/10.5555/148286" xsd:anyURI {comment="William H. Press, Saul A. Teukolsky, William T. Vetterling & Brian P. Flannery. Numerical Recipes in C. The Art of Scientific Computing, 2nd Edition, 1992. Chapter 16. Pages 719."}
+property_value: skos:altLabel "rkqs" xsd:string
+property_value: skos:definition "Cash-Karp method with step size adjustment." xsd:string
+
+[Term]
+id: kisao:KISAO_0000673
+name: skip reactions that produce negative species amounts
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: skos:definition "Parameter which instructs a simulation tool to skip reactions that would result in negative amounts of species." xsd:string
+
+[Term]
+id: kisao:KISAO_0000674
+name: presimulate
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: skos:definition "Whether a model should be presimulated prior to analysis." xsd:string
+
+[Term]
+id: kisao:KISAO_0000675
+name: Broyden method
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: skos:definition "Family of Quasi-Newton methods for finding roots in k variables originally described by C. G. Broyden in 1965." xsd:string
+
+[Term]
+id: kisao:KISAO_0000676
+name: degree of linearity
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: skos:definition "The degree of linearity of a system." xsd:string
+
+[Term]
+id: kisao:KISAO_0000677
+name: maximum number of steps for presimulation
+is_a: kisao:KISAO_0000415 ! maximum number of steps
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: skos:definition "Maximum number of steps to take in presimulating a model prior to analysis." xsd:string
+
+[Term]
+id: kisao:KISAO_0000678
+name: maximum number of steps for approximation
+is_a: kisao:KISAO_0000415 ! maximum number of steps
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: skos:definition "Maximum number of steps to take in approximating an analysis." xsd:string
+
+[Term]
+id: kisao:KISAO_0000679
+name: maximum time for approximation
+is_a: kisao:KISAO_0000681 ! maximum time
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: skos:definition "Maximum amount of time to spend approximating an analysis." xsd:string
+
+[Term]
+id: kisao:KISAO_0000680
+name: duration
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: skos:definition "Length of time to simulate." xsd:string
+
+[Term]
+id: kisao:KISAO_0000681
+name: maximum time
+is_a: kisao:KISAO_0000244 ! granularity control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: skos:definition "Maximum amount of wall time for an operation." xsd:string
+
+[Term]
+id: kisao:KISAO_0000682
+name: allow approximation
+is_a: kisao:KISAO_0000243 ! method switching control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: skos:definition "Whether to find an approximate solution if an exact solution could not be found." xsd:string
+
+[Term]
+id: kisao:KISAO_0000683
+name: relative tolerance for approximation
+is_a: kisao:KISAO_0000209 ! relative tolerance
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: skos:definition "Relatative tolerance for an alternative approximate solution to an exact solution which could not be found." xsd:string
+
+[Term]
+id: kisao:KISAO_0000684
+name: number of steps per output
+is_a: kisao:KISAO_0000244 ! granularity control parameter
+property_value: dc:creator "JRK" xsd:string
+property_value: kisao:isImplementedIn "http://identifiers.org/biosimulators/bionetgen" xsd:anyURI {comment="BioNetgen"}
+property_value: skos:definition "Number of simulation steps between each simulation output." xsd:string
+
+[Term]
+id: kisao:KISAO_0000685
+name: biological state optimization method
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000690 ! biological system
+property_value: dc:creator "EN" xsd:string
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "WL" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A method for computing the optimal state of a biological system according to a particular objective." xsd:string
+
+[Term]
+id: kisao:KISAO_0000686
+name: Enzyme Cost Minimization
+is_a: kisao:KISAO_0000685 ! biological state optimization method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000691 ! metabolic system
+property_value: dc:creator "EN" xsd:string
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+property_value: kisao:isImplementedIn "https://gitlab.com/equilibrator/metabolic-pathway-analysis" xsd:anyURI {comment="Metabolic Pathway Analysis"}
+property_value: seeAlso "http://identifiers.org/doi:10.1371/journal.pcbi.1005167" xsd:anyURI {comment="Elad Noor, Avi Flamholz, Arren Bar-Even, Dan Davidi, Ron Milo & Wolfram Liebermeister. The Protein Cost of Metabolic Fluxes: Prediction from Enzymatic Rate Laws and Cost Minimization. PLoS Comput Biol 12 (11): e1005167 (2016)."}
+property_value: skos:altLabel "ECM" xsd:string
+property_value: skos:definition "For a given metabolic network model, the Enzyme Cost Minimization method determines plausible metabolite and enzyme concentrations (which determine thermodynamic forces and enzyme catalytic rates). Fluxes, enzyme kinetic constants, admissible metabolite concentration ranges, and enzyme cost weights (e.g. enzyme molecular masses) are given as input data. The method applies the principle that high enzyme (or enzyme plus metabolite) concentrations must be avoided, and maximizes a weighted sum of enzyme and  metabolite concentrations." xsd:string
+
+[Term]
+id: kisao:KISAO_0000687
+name: Max-min Driving Force method
+is_a: kisao:KISAO_0000685 ! biological state optimization method
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000106 ! continuous variable
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000691 ! metabolic system
+property_value: dc:creator "EN" xsd:string
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "WL" xsd:string
+property_value: kisao:isImplementedIn "https://gitlab.com/equilibrator/metabolic-pathway-analysis" xsd:anyURI {comment="Metabolic Pathway Analysis"}
+property_value: seeAlso "http://identifiers.org/doi:10.1371/journal.pcbi.1003483" xsd:anyURI {comment="Elad Noor, Arren Bar-Even, Avi Flamholz, Ed Reznik, Wolfram Liebermeister & Ron Milo. Pathway thermodynamics highlights kinetic obstacles in central metabolism. PLOS Computational Biology 10(2): e1003483 (2014)."}
+property_value: skos:altLabel "MDF" xsd:string
+property_value: skos:definition "For a given metabolic network model, the MDF method determines plausible metabolite concentrations and thermodynamic forces. Flux directions, equilibrium constants (or equivalently, standard Gibbs free energies of reactions) and admissible metabolite concentration ranges are given as input data. The method applies the principle that low thermodynamic forces must be avoided, and maximizes the minimum thermodynamic force across the entire network." xsd:string
+
+[Term]
+id: kisao:KISAO_0000688
+name: type of system described
+is_a: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+property_value: dc:creator "EN" xsd:string
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "WL" xsd:string
+
+[Term]
+id: kisao:KISAO_0000689
+name: mathematical system
+is_a: kisao:KISAO_0000688 ! type of system described
+property_value: dc:creator "EN" xsd:string
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "WL" xsd:string
+
+[Term]
+id: kisao:KISAO_0000690
+name: biological system
+is_a: kisao:KISAO_0000688 ! type of system described
+property_value: dc:creator "EN" xsd:string
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "WL" xsd:string
+
+[Term]
+id: kisao:KISAO_0000691
+name: metabolic system
+is_a: kisao:KISAO_0000690 ! biological system
+property_value: dc:creator "EN" xsd:string
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "WL" xsd:string
+
+[Term]
+id: kisao:KISAO_0000692
+name: cellular system
+is_a: kisao:KISAO_0000690 ! biological system
+property_value: dc:creator "EN" xsd:string
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "WL" xsd:string
+
+[Term]
+id: kisao:KISAO_0000693
+name: biochemical system
+is_a: kisao:KISAO_0000690 ! biological system
+property_value: dc:creator "EN" xsd:string
+property_value: dc:creator "JRK" xsd:string
+property_value: dc:creator "WL" xsd:string
+
+[Term]
+id: kisao:KISAO_0000694
+name: ODE solver
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000209 {maxCardinality="1"} ! relative tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000211 {maxCardinality="1"} ! absolute tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000415 {maxCardinality="1"} ! maximum number of steps
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000475 {maxCardinality="1"} ! integration method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000476 {maxCardinality="1"} ! iteration type
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000477 {maxCardinality="1"} ! linear solver
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000478 {maxCardinality="1"} ! preconditioner
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000479 {maxCardinality="1"} ! upper half-bandwidth
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000480 {maxCardinality="1"} ! lower half-bandwidth
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000481 {maxCardinality="1"} ! interpolate solution
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000543 {maxCardinality="1"} ! stability limit detection flag
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000570 {maxCardinality="1"} ! auto reduce tolerances
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000571 {maxCardinality="1"} ! absolute tolerance adjustment factor
+property_value: dc:creator "lps" xsd:string
+property_value: kisao:isOrganizational "false" xsd:boolean
+property_value: skos:altLabel "ordinary differential equation solver" xsd:string {comment="EXACT"}
+property_value: skos:definition "An ODE solver is the general category of packages such as CVODE-like methods [http://identifiers.org/biomodels.kisao/KISAO_0000433] or Livermore solvers [http://identifiers.org/biomodels.kisao/KISAO_0000094] that solve systems of ordinary differential equations." xsd:string
+
+[Term]
+id: kisao:KISAO_0000695
+name: parameters for
+is_a: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+property_value: dc:created "2023/05/19" xsd:string
+property_value: dc:creator "lps" xsd:string
+property_value: skos:definition "The children parameters of this term are applied when the parent general term is implented as the more-specific value of this term.  For example:  a 'parameters for' term might be used as a child of an 'ODE Solver' ([http://identifiers.org/biomodels.kisao/KISAO_0000694]), have a value of 'KISAO_0000019' (CVODE)', and have a child term 'use stiff method' of 'true' ([http://identifiers.org/biomodels.kisao/KISAO_0000671])" xsd:string
+
+[Term]
+id: kisao:KISAO_0000696
+name: steady state root-finding problem
+is_a: kisao:KISAO_0000370 ! type of problem
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:altLabel "steady state problem" xsd:string {comment="EXACT"}
+
+[Term]
+id: kisao:KISAO_0000697
+name: SDE solver
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000104 ! stochastic system behaviour
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000108 ! progression with fixed time step
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000237 ! approximate solution
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000371 ! stochastic differential equation problem
+property_value: dc:creator "lps" xsd:string
+property_value: kisao:isOrganizational "false" xsd:boolean
+property_value: skos:altLabel "stochastic differential equation solver" xsd:string {comment="EXACT"}
+property_value: skos:definition "An SDE solver is the general category of packages that provide stochastic solutions to a system of differential equations with propensities." xsd:string
+
+[Term]
+id: kisao:KISAO_0000698
+name: particle coordinates
+is_a: kisao:KISAO_0000831 ! model and simulation property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000822 ! extensive property
+property_value: dc:created "12-08-2023" xsd:string
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The set of coordinates for all particles of these entities." xsd:string
+
+[Term]
+id: kisao:KISAO_0000699
+name: DAE Solver
+is_a: kisao:KISAO_0000000 ! modelling and simulation algorithm
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000373 ! differential-algebraic equation problem
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000374 ! ordinary differential equation problem
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000209 {maxCardinality="1"} ! relative tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000211 {maxCardinality="1"} ! absolute tolerance
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000415 {maxCardinality="1"} ! maximum number of steps
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000475 {maxCardinality="1"} ! integration method
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000476 {maxCardinality="1"} ! iteration type
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000477 {maxCardinality="1"} ! linear solver
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000478 {maxCardinality="1"} ! preconditioner
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000479 {maxCardinality="1"} ! upper half-bandwidth
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000480 {maxCardinality="1"} ! lower half-bandwidth
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000481 {maxCardinality="1"} ! interpolate solution
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000543 {maxCardinality="1"} ! stability limit detection flag
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000570 {maxCardinality="1"} ! auto reduce tolerances
+relationship: kisao:KISAO_0000259 kisao:KISAO_0000571 {maxCardinality="1"} ! absolute tolerance adjustment factor
+property_value: dc:created "2024-03-13" xsd:string
+property_value: dc:creator "lps" xsd:string
+property_value: kisao:isOrganizational "false" xsd:boolean
+property_value: skos:altLabel "differential algebraic equation solver" xsd:string {comment="EXACT"}
+property_value: skos:definition "A DAE solver is the general category of packages such as IDA-like methods [http://identifiers.org/biomodels.kisao/KISAO_0000432] that solve systems of differential algebraic equations (DAEs).  DAEs are a superset of ODEs that may additionally contain algebraic equations or 'fast' reactions." xsd:string
+
+[Term]
+id: kisao:KISAO_0000800
+name: systems property
+is_a: kisao:KISAO_0000831 ! model and simulation property
+disjoint_from: kisao:KISAO_0000801 ! concentration control coefficient matrix (unscaled)
+property_value: dc:creator "LPS" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A systems-level property of an entire model or simulation." xsd:string
+
+[Term]
+id: kisao:KISAO_0000801
+name: concentration control coefficient matrix (unscaled)
+is_a: kisao:KISAO_0000800 ! systems property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000635 ! unscaled property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The unscaled concentration control coefficient matrix. The dimensions are species by reactions." xsd:string
+
+[Term]
+id: kisao:KISAO_0000802
+name: control coefficient (scaled)
+is_a: kisao:KISAO_0000800 ! systems property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000634 ! scaled property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "A scaled control coefficient of any dependent element (such as a reaction or a floating species) with respect to an independent element (such as a global parameter or boundary species)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000803
+name: control coefficient (unscaled)
+is_a: kisao:KISAO_0000800 ! systems property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000635 ! unscaled property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "An unscaled control coefficient of any dependent element (such as a reaction or a floating species) with respect to an independent element (such as a global parameter or boundary species)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000804
+name: elasticity matrix (unscaled)
+is_a: kisao:KISAO_0000800 ! systems property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000635 ! unscaled property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The unscaled elasticity matrix. The dimensions are reactions by species." xsd:string
+
+[Term]
+id: kisao:KISAO_0000805
+name: elasticity coefficient (unscaled)
+is_a: kisao:KISAO_0000800 ! systems property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000635 ! unscaled property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "An unscaled elasticity coefficient of any reaction with respect to an independent element (such as a global parameter or boundary species)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000806
+name: elasticity matrix (scaled)
+is_a: kisao:KISAO_0000800 ! systems property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000634 ! scaled property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The scaled elasticity matrix. The dimensions are reactions by species." xsd:string
+
+[Term]
+id: kisao:KISAO_0000807
+name: elasticity coefficient (scaled)
+is_a: kisao:KISAO_0000800 ! systems property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000634 ! scaled property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "A scaled elasticity coefficient of any reaction with respect to an independent element (such as a global parameter or boundary species)." xsd:string
+
+[Term]
+id: kisao:KISAO_0000808
+name: reduced stoichiometry matrix
+is_a: kisao:KISAO_0000800 ! systems property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The reduced stoichiometry matrix. The dimensions are species by reactions." xsd:string
+
+[Term]
+id: kisao:KISAO_0000809
+name: reduced Jacobian matrix
+is_a: kisao:KISAO_0000800 ! systems property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The reduced Jacobian matrix. The dimensions are species by species." xsd:string
+
+[Term]
+id: kisao:KISAO_0000810
+name: reduced eigenvalue matrix
+is_a: kisao:KISAO_0000800 ! systems property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The reduced eigenvalue matrix of a model. The dimensions are species by two, where the first column is the real part of the eigenvalues, and the second column is the imaginary part of the eigenvalues." xsd:string
+
+[Term]
+id: kisao:KISAO_0000811
+name: stoichiometry matrix
+is_a: kisao:KISAO_0000800 ! systems property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:altLabel "full stochiometry matrix" xsd:string
+property_value: skos:definition "The (full) stoichiometry matrix. The dimensions are species by reactions." xsd:string
+
+[Term]
+id: kisao:KISAO_0000812
+name: Jacobian matrix
+is_a: kisao:KISAO_0000800 ! systems property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:altLabel "full Jacobian matrix" xsd:string
+property_value: skos:definition "The (full) Jacobian matrix. The dimensions are species by species." xsd:string
+
+[Term]
+id: kisao:KISAO_0000813
+name: Eigenvalue matrix
+is_a: kisao:KISAO_0000800 ! systems property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:altLabel "full eigenvalue matrix" xsd:string
+property_value: skos:definition "The (full) eigenvalue matrix of a model. The dimensions are species by two, where the first column is the real part of the eigenvalues, and the second column is the imaginary part of the eigenvalues." xsd:string
+
+[Term]
+id: kisao:KISAO_0000814
+name: flux control coefficient matrix (unscaled)
+is_a: kisao:KISAO_0000800 ! systems property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000635 ! unscaled property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The unscaled flux control coefficient matrix. The dimensions are reactions by reactions." xsd:string
+
+[Term]
+id: kisao:KISAO_0000815
+name: flux control coefficient matrix (scaled)
+is_a: kisao:KISAO_0000800 ! systems property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000634 ! scaled property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The scaled flux control coefficient matrix. The dimensions are reactions by reactions." xsd:string
+
+[Term]
+id: kisao:KISAO_0000816
+name: link matrix
+is_a: kisao:KISAO_0000800 ! systems property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The link matrix of a model." xsd:string
+
+[Term]
+id: kisao:KISAO_0000817
+name: kernel matrix
+is_a: kisao:KISAO_0000800 ! systems property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The Kernel matrix of a model." xsd:string
+
+[Term]
+id: kisao:KISAO_0000818
+name: L0 matrix
+is_a: kisao:KISAO_0000800 ! systems property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The L0 matrix of a model." xsd:string
+
+[Term]
+id: kisao:KISAO_0000819
+name: Nr matrix
+is_a: kisao:KISAO_0000800 ! systems property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The Nr matrix of a model." xsd:string
+
+[Term]
+id: kisao:KISAO_0000820
+name: model and simulation property characteristic
+property_value: dc:creator "LPS" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A property of a variable of a model or simulation." xsd:string
+
+[Term]
+id: kisao:KISAO_0000821
+name: intensive property
+is_a: kisao:KISAO_0000820 ! model and simulation property characteristic
+property_value: dc:creator "LPS" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: seeAlso "https://en.wikipedia.org/wiki/Intensive_and_extensive_properties" xsd:anyURI
+property_value: skos:definition "An intensive variable such as a concentration or temperature." xsd:string
+
+[Term]
+id: kisao:KISAO_0000822
+name: extensive property
+is_a: kisao:KISAO_0000820 ! model and simulation property characteristic
+property_value: dc:creator "LPS" xsd:string
+property_value: seeAlso "https://en.wikipedia.org/wiki/Intensive_and_extensive_properties" xsd:anyURI
+property_value: skos:definition "An extensive variable such as an amount, particle number, or mass." xsd:string
+
+[Term]
+id: kisao:KISAO_0000824
+name: aggregation function
+is_a: kisao:KISAO_0000633 ! computational function
+property_value: dc:creator "LPS" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A function that aggregates a set of results, reducing its dimension(s). Examples include functions that compute minima or maxima of sets of values." xsd:string
+
+[Term]
+id: kisao:KISAO_0000825
+name: mean ignoring NaN
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "LPS, MK" xsd:string
+property_value: skos:definition "The mean (average) of a set of values, ignoring NaN entries." xsd:string
+
+[Term]
+id: kisao:KISAO_0000826
+name: standard deviation ignoring NaN
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "LPS, MK" xsd:string
+property_value: skos:definition "The standard deviation of a set of values, ignoring NaN entries." xsd:string
+
+[Term]
+id: kisao:KISAO_0000827
+name: standard error ignoring NaN
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "LPS, MK" xsd:string
+property_value: skos:definition "The standard error of a set of values, ignoring NaN entries." xsd:string
+
+[Term]
+id: kisao:KISAO_0000828
+name: maximum ignoring NaN
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "LPS, MK" xsd:string
+property_value: skos:definition "The maximum value of a set of values, ignoring NaN entries." xsd:string
+
+[Term]
+id: kisao:KISAO_0000829
+name: minimum ignoring NaN
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "LPS, MK" xsd:string
+property_value: skos:definition "The minimum value of a set of values, ignoring NaN entries." xsd:string
+
+[Term]
+id: kisao:KISAO_0000830
+name: maximum
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The maximum of a set of values. If the values contain NaN the maximum is NaN." xsd:string
+
+[Term]
+id: kisao:KISAO_0000831
+name: model and simulation property
+property_value: dc:creator "LPS" xsd:string
+property_value: kisao:isOrganizational "true" xsd:boolean
+property_value: skos:definition "A variable of a model or simulation." xsd:string
+
+[Term]
+id: kisao:KISAO_0000832
+name: time
+is_a: kisao:KISAO_0000831 ! model and simulation property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The implied time variable of the model state." xsd:string
+
+[Term]
+id: kisao:KISAO_0000834
+name: rate of change
+is_a: kisao:KISAO_0000831 ! model and simulation property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000647 ! derivative
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000655 ! rate
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:altLabel "rate" xsd:string
+property_value: skos:definition "The rate of change of one variable with respect to a second variable." xsd:string
+
+[Term]
+id: kisao:KISAO_0000835
+name: concentration control coefficient matrix (scaled)
+is_a: kisao:KISAO_0000800 ! systems property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000634 ! scaled property
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The scaled concentration control coefficient matrix. The dimensions are species by reactions." xsd:string
+
+[Term]
+id: kisao:KISAO_0000836
+name: amount
+is_a: kisao:KISAO_0000831 ! model and simulation property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000822 ! extensive property
+property_value: dc:created "2021-06-03" xsd:string
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The extensive quantity amount." xsd:string
+
+[Term]
+id: kisao:KISAO_0000837
+name: particle number
+is_a: kisao:KISAO_0000831 ! model and simulation property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000822 ! extensive property
+property_value: dc:created "2021-06-03" xsd:string
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The extensive quantity particle number, or, the molar amount of the entity multiplied by Avogadro's number." xsd:string
+
+[Term]
+id: kisao:KISAO_0000838
+name: concentration
+is_a: kisao:KISAO_0000831 ! model and simulation property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000821 ! intensive property
+property_value: dc:created "2021-06-03" xsd:string
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The intensive quantity concentration, or, the amount of the entity with respect to the entity in which it resides." xsd:string
+
+[Term]
+id: kisao:KISAO_0000839
+name: temperature
+is_a: kisao:KISAO_0000831 ! model and simulation property
+relationship: kisao:KISAO_0000245 kisao:KISAO_0000821 ! intensive property
+property_value: dc:created "2021-06-03" xsd:string
+property_value: dc:creator "LPS" xsd:string
+property_value: skos:definition "The intensive quantity temperature." xsd:string
+
+[Term]
+id: kisao:KISAO_0000840
+name: minimum
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The minimum of a set of values. If the values contain NaN the minimum is NaN." xsd:string
+
+[Term]
+id: kisao:KISAO_0000841
+name: mean
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The mean of a set of values. If the values contain NaN the mean is NaN." xsd:string
+
+[Term]
+id: kisao:KISAO_0000842
+name: standard deviation
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The standard deviation of a set of values. If the values contain NaN the standard deviation is NaN." xsd:string
+
+[Term]
+id: kisao:KISAO_0000843
+name: standard error
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The standard error of a set of values. If the values contain NaN the standard deviation is NaN." xsd:string
+
+[Term]
+id: kisao:KISAO_0000844
+name: sum ignoring NaN
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The sum of a set of values, ignoring Nan entries." xsd:string
+
+[Term]
+id: kisao:KISAO_0000845
+name: sum
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The sum of a set of values. If the values contain NaN the sum is NaN." xsd:string
+
+[Term]
+id: kisao:KISAO_0000846
+name: product ignoring NaN
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The product of a set of values, ignoring Nan entries." xsd:string
+
+[Term]
+id: kisao:KISAO_0000847
+name: product
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The product of a set of values. If the values contain NaN the product is NaN." xsd:string
+
+[Term]
+id: kisao:KISAO_0000848
+name: cumulative sum ignoring NaN
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The cumulative sum of a set of values, ignoring Nan entries." xsd:string
+
+[Term]
+id: kisao:KISAO_0000849
+name: cumulative sum
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The cumulative sum of a set of values. If the values contain NaN the cumulative sum is NaN." xsd:string
+
+[Term]
+id: kisao:KISAO_0000850
+name: cumulative product ignoring NaN
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The cumulative product of a set of values, ignoring Nan entries." xsd:string
+
+[Term]
+id: kisao:KISAO_0000851
+name: cumulative product
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The cumulative product of a set of values. If the values contain NaN the cumulative product is NaN." xsd:string
+
+[Term]
+id: kisao:KISAO_0000852
+name: count ignoring NaN
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The number of non-zero elements of a set of values, ignoring Nan entries." xsd:string
+
+[Term]
+id: kisao:KISAO_0000853
+name: count
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The number of non-zero elements of a set of values. If the values contain NaN the count is NaN." xsd:string
+
+[Term]
+id: kisao:KISAO_0000854
+name: length ignoring NaN
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The number of elements of a set of values, ignoring Nan entries." xsd:string
+
+[Term]
+id: kisao:KISAO_0000855
+name: length
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The number of elements of a set of values." xsd:string
+
+[Term]
+id: kisao:KISAO_0000856
+name: median ignoring NaN
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The median of a set of values, ignoring Nan entries." xsd:string
+
+[Term]
+id: kisao:KISAO_0000857
+name: median
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The median of a set of values. If the values contain NaN the median is NaN." xsd:string
+
+[Term]
+id: kisao:KISAO_0000858
+name: variance ignoring NaN
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The variance of a set of values, ignoring Nan entries." xsd:string
+
+[Term]
+id: kisao:KISAO_0000859
+name: variance
+is_a: kisao:KISAO_0000824 ! aggregation function
+property_value: dc:creator "MK" xsd:string
+property_value: skos:definition "The variance of a set of values. If the values contain NaN the variance is NaN." xsd:string
 
 [Typedef]
-id: KISAO_0000245
+id: kisao:KISAO_0000245
 name: has characteristic
-property_value: definition "'has characteristic' links algorithms to the characteristics, they possess." xsd:string
-domain: KISAO_0000000 ! modelling and simulation algorithm
-disjoint_from: KISAO_0000360 ! uses
-inverse_of: KISAO_0000268 ! is characteristic of
+property_value: skos:definition "'has characteristic' links algorithms to the characteristics they possess." xsd:string
+domain: kisao:KISAO_0000000 ! modelling and simulation algorithm
+range: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+disjoint_from: kisao:KISAO_0000360 ! uses
+inverse_of: kisao:KISAO_0000268 ! is characteristic of
 
 [Typedef]
-id: KISAO_0000246
+id: kisao:KISAO_0000246
 name: is hybrid of
-property_value: definition "The basic idea of hybrid simulation methods is to combine the advantages of complementary simulation approaches: the whole system is subdivided into appropriate parts and different simulation methods operate on these parts at the same time.\n'is hybrid of' is a relation between the complex simulation method and algorithms it applies to the different parts of the system." xsd:string
 property_value: seeAlso "http://identifiers.org/doi/10.1093/bib/bbn050" xsd:anyURI {comment="Biochemical simulations: stochastic, approximate stochastic and hybrid approaches. Pahle J. Brief Bioinform. 2009 Jan;10(1):53-64. Epub 2009 Jan 16."}
-range: KISAO_0000000 ! modelling and simulation algorithm
-is_a: KISAO_0000360 ! uses
+property_value: skos:definition "The basic idea of hybrid simulation methods is to combine the advantages of complementary simulation approaches: the whole system is subdivided into appropriate parts and different simulation methods operate on these parts at the same time.\n'is hybrid of' is a relation between the complex simulation method and algorithms it applies to the different parts of the system." xsd:string
+range: kisao:KISAO_0000000 ! modelling and simulation algorithm
+is_a: kisao:KISAO_0000360 ! uses
 
 [Typedef]
-id: KISAO_0000250
+id: kisao:KISAO_0000250
 name: is parameter of
-property_value: definition "'is parameter of' is an inverse of 'has parameter' and links parameters to the algorithms which use them." xsd:string
-range: KISAO_0000000 ! modelling and simulation algorithm
-inverse_of: KISAO_0000259 ! has parameter
+property_value: skos:definition "'is parameter of' is an inverse of 'has parameter' and links parameters to the algorithms which use them." xsd:string
+domain: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
+range: kisao:KISAO_0000000 ! modelling and simulation algorithm
+inverse_of: kisao:KISAO_0000259 ! has parameter
 
 [Typedef]
-id: KISAO_0000259
+id: kisao:KISAO_0000259
 name: has parameter
-property_value: definition "'has parameter' links algorithms to the parameters they use." xsd:string
-domain: KISAO_0000000 ! modelling and simulation algorithm
+property_value: skos:definition "'has parameter' links algorithms to the parameters they use." xsd:string
+domain: kisao:KISAO_0000000 ! modelling and simulation algorithm
+range: kisao:KISAO_0000201 ! modelling and simulation algorithm parameter
 
 [Typedef]
-id: KISAO_0000268
+id: kisao:KISAO_0000268
 name: is characteristic of
-property_value: definition "'is characteristic of' is an inverse of 'has characteristic' and links characteristics to the algorithms which possess them." xsd:string
-range: KISAO_0000000 ! modelling and simulation algorithm
+property_value: skos:definition "'is characteristic of' is an inverse of 'has characteristic' and links characteristics to the algorithms which possess them." xsd:string
+domain: kisao:KISAO_0000097 ! modelling and simulation algorithm characteristic
+range: kisao:KISAO_0000000 ! modelling and simulation algorithm
 
 [Typedef]
-id: KISAO_0000359
+id: kisao:KISAO_0000359
 name: is similar to
-property_value: definition "A relationship indicating that two entities are similar to each other." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "A relationship indicating that two entities are similar to each other." xsd:string
 is_reflexive: true
 is_symmetric: true
 
 [Typedef]
-id: KISAO_0000360
+id: kisao:KISAO_0000360
 name: uses
-property_value: definition "A relation between algorithms indicating that one algorithm uses another one (for example, if the algorithm switches between several algorithms)." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-domain: KISAO_0000000 ! modelling and simulation algorithm
-range: KISAO_0000000 ! modelling and simulation algorithm
-inverse_of: KISAO_0000399 ! is used by
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "A relation between algorithms indicating that one algorithm uses another one (for example, if the algorithm switches between several algorithms)." xsd:string
+domain: kisao:KISAO_0000000 ! modelling and simulation algorithm
+range: kisao:KISAO_0000000 ! modelling and simulation algorithm
+inverse_of: kisao:KISAO_0000399 ! is used by
 
 [Typedef]
-id: KISAO_0000361
+id: kisao:KISAO_0000361
 name: is generalization of
-property_value: definition "A relation between kinetic simulation algorithms, indicating that one is a generalization of another (e.g.if one extends another to suit systems with more general characteristics )." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
-domain: KISAO_0000000 ! modelling and simulation algorithm
-range: KISAO_0000000 ! modelling and simulation algorithm
-is_a: KISAO_0000359 ! is similar to
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "A relation between kinetic simulation algorithms, indicating that one is a generalization of another (e.g.if one extends another to suit systems with more general characteristics )." xsd:string
+domain: kisao:KISAO_0000000 ! modelling and simulation algorithm
+range: kisao:KISAO_0000000 ! modelling and simulation algorithm
+is_a: kisao:KISAO_0000359 ! is similar to
 
 [Typedef]
-id: KISAO_0000399
+id: kisao:KISAO_0000399
 name: is used by
-property_value: definition "A relation between algorithms indicating that one algorithm is used by another one (for example, if the algorithm switches between several algorithms). 'is used by' is inverse of 'uses'." xsd:string
-property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: dc:creator "AZ" xsd:string
+property_value: skos:definition "A relation between algorithms indicating that one algorithm is used by another one (for example, if the algorithm switches between several algorithms). 'is used by' is inverse of 'uses'." xsd:string
 
diff --git a/vcell-core/src/main/resources/kisao_algs_old_replaced_22Nov2024.obo b/vcell-core/src/main/resources/kisao_algs_old_replaced_22Nov2024.obo
new file mode 100644
index 0000000000..b022707c32
--- /dev/null
+++ b/vcell-core/src/main/resources/kisao_algs_old_replaced_22Nov2024.obo
@@ -0,0 +1,2847 @@
+format-version: 1.2
+remark: This is a core version which contains all but deprecated classes.
+ontology: http://www.biomodels.net/kisao/KISAO#
+property_value: defaultLanguage "en" xsd:string
+property_value: definition "The Kinetic Simulation Algorithm Ontology (KiSAO) classifies algorithms available for the simulation and analysis of models in biology, and their characteristics and the parameters required for their use." xsd:string
+property_value: http://purl.org/dc/terms/rights "Artistic License 2.0" xsd:string
+property_value: owl:versionInfo "2.30" xsd:decimal
+property_value: seeAlso "http://co.mbine.org/standards/kisao" xsd:anyURI
+property_value: seeAlso "http://identifiers.org/pubmed/22027554" xsd:anyURI
+owl-axioms: 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<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000027>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000027> \"2007-11-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000028> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000028>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000029> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000029>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000029> \"2007-11-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000032> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000032>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000032> \"2007-11-12\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000032> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000033> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000033>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000033> \"2007-11-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000038> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000038>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000039> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000039>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000039> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000040> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000040>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000045> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000045>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000045> \"2007-10-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000046> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000046>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000046> \"2007-10-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000048> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000048>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000051> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000051>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000056> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000056>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000056> \"2007-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000064> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000064>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000064> \"2007-11-12\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000071> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000071>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000071> \"2007-11-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000074> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000074>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000074> \"2007-10-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000075> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000075>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000081> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000081>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000082> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000082>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000084> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000084>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000086> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000086>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000087> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000087>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000087> \"2007-11-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000088> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000088>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000088> \"2007-11-30\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000089> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000089>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000089> \"2007-10-27\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000090> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000090>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000091> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000091>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000091> \"2007-11-30\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000093> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000093>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000093> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000094>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000095> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000095>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000095> \"2008-07-08\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000231> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000231>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000232> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000232>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000233> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000233>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000234> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000234>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000241> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000241>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000261> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000261>)\n\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000261> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000359> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"1\"^^xsd:integer))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000264> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000264>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000264> \"2011-04-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000273>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> \"2011-05-05\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000274> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000274>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000274> \"2011-05-05\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000276> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000276>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000276> \"2011-05-09\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000276> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000278> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000278>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000278> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000279> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000279>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000279> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000280> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000280>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000280> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000281>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000282> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000282>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000282> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000283> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000283>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000283> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000285> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000285>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000285> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000286> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000286>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000286> \"2011-05-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000287> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000287>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000287> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000288> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000288>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000288> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000289> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000289>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000289> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000290> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000290>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000290> \"2011-05-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000290> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000296> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000296>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000296> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000297> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000297>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000297> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000299> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000299>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000299> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000301> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000301>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000301> \"2011-05-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000301> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"2\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000302> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000302>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000302> \"2011-05-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000303> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000303>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000303> \"2011-05-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000303> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"3\"^^xsd:integer))))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000303> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000304> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000304>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000304> \"2011-05-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000305> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000305>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000305> \"2011-05-10\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000305> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"5\"^^xsd:integer))))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000305> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"6\"^^xsd:integer))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000306>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> \"2011-05-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000307> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000307>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000307> \"2011-05-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000310> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000310>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000310> \"2011-05-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000314>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> \"2011-05-20\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000317> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000317>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000317> \"2011-05-23\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000318> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000318>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000318> \"2011-05-26\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000319>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> \"2011-05-26\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000320> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000320>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000320> \"2011-05-26\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000321> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000321>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000321> \"2011-05-26\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000323> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000323>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000323> \"2011-06-02\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000324> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000324>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000324> \"2011-06-02\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000329> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000329>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000329> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000330> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000330>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000330> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000331> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000331>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000331> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000333> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000333>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000333> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000335> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000335>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000335> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000336> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000336>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000336> \"2011-06-03\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000337> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000337>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000337> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000338> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000338>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000338> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000339> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000339>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000339> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000341> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000341>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000341> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000342> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000342>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000342> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000343> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000343>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000343> \"2011-06-07\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000345> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000345>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000345> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000348> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000348>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000348> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000349> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000349>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000349> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000350> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000350>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000350> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000351> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000351>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000351> \"2011-06-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000353> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000353>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000353> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000355> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000355>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000355> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000356> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000356>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000356> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000357> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000357>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000357> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000358> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000358>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000358> \"2011-06-10\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000363>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> \"2011-06-13\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000364> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000364>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000364> \"2011-06-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000365> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000365>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000365> \"2011-06-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000367> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000367>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000367> \"2011-06-16\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000369>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> \"2011-06-27\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000377>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> \"2011-06-30\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000378> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000378>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000378> \"2011-06-30\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000378> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"2\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000380> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000380>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000380> \"2011-07-01\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000381> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000381>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000381> \"2011-07-01\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000381> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"2\"^^xsd:integer))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000382> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000382>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000382> \"2011-07-01\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000384> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000384>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000384> \"2011-07-01\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000388> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000388>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000388> \"2011-07-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000395> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000395>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000395> \"2011-07-19\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000397>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> \"2011-07-19\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000398>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> \"2011-07-19\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000407>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> \"2012-01-17\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000408>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000409> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000409>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000409> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000410> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000410>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000410> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000411> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000411>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000411> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000412> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000412>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000412> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000413> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000413>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000413> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000416> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000416>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000416> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000417> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000417>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000417> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000418> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000418>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000418> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000419>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> \"2012-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000432> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000432>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000432> \"2012-05-24\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000433>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> \"2012-05-24\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000433> ObjectUnionOf(ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> <http://www.biomodels.net/kisao/KISAO#KISAO_0000280>) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> <http://www.biomodels.net/kisao/KISAO#KISAO_0000288>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000434> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000434>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000434> \"2012-09-25\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000435> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000435>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000435> \"2012-09-26\"^^xsd:date)\nEquivalentClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000435> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000302> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"4\"^^xsd:integer))) ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"5\"^^xsd:integer)))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000436> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000436>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000436> \"2012-09-26\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000436> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"5\"^^xsd:integer))))\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000436> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000360> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> DataHasValue(<http://www.biomodels.net/kisao/KISAO#KISAO_0000275> \"8\"^^xsd:integer))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000437> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000437>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000437> \"2012-11-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000447> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000447>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000447> \"2013-01-28\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000447> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000015> <http://www.biomodels.net/kisao/KISAO#KISAO_0000039>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000448> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000448>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000448> \"2013-01-28\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000468> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000468>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000468> \"2014-04-25\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000470> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000470>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000470> \"2015-04-23\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000473> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000473>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000473> \"2015-04-23\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000491> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000491>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000496> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000496>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000497> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000497>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000497> \"2017-01-09\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000499> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000499>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000499> \"2017-09-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000500> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000500>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000500> \"2017-09-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000501> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000501>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000501> \"2017-09-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000502> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000502>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000502> \"2017-09-12\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000503> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000503>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000503> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000504> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000504>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000504> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000505> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000505>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000505> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000510> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000510>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000510> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000511> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000511>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000511> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000512> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000512>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000512> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000513> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000513>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000513> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000514> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000514>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000514> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000515> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000515>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000515> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000516> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000516>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000516> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000520> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000520>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000520> \"2019-01-18\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000524> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000524>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000524> \"2020-05-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000526> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000526>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000526> \"2020-08-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000527> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000527>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000527> \"2020-08-11\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000535> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000535>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000535> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000536> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000536>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000536> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000560> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000560>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000560> \"2020-10-29\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000560> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000088> <http://www.biomodels.net/kisao/KISAO#KISAO_0000089>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000561> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000561>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000561> \"2020-10-29\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000561> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000032>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000562> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000562>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000562> \"2020-10-29\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000562> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000088>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000563> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000563>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000563> \"2020-10-29\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000563> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000086>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000573> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000573>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000573> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000575> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000575>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000575> \"2020-11-06\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000575> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000039> ObjectUnionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> <http://www.biomodels.net/kisao/KISAO#KISAO_0000088> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281>))))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000580> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000580>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000580> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000588> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000588>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000588> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000591> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000591>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000591> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000593> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000593>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000593> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000595> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000595>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000595> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000596> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000596>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000596> \"2020-10-29\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000598> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000598>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000598> \"2021-01-13\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000598> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000287>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000599> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000599>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000599> \"2021-01-13\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000599> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000286>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000600> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000600>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000600> \"2021-01-13\"^^xsd:date)\nSubClassOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000600> ObjectSomeValuesFrom(<http://www.biomodels.net/kisao/KISAO#KISAO_0000246> ObjectIntersectionOf(<http://www.biomodels.net/kisao/KISAO#KISAO_0000027> <http://www.biomodels.net/kisao/KISAO#KISAO_0000287>)))\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000606> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000606>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000606> \"2021-01-25\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000608> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000608>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000608> \"2021-01-25\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000610> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000610>)\n\nAnnotationAssertion(<http://purl.org/dc/terms/created> <http://www.biomodels.net/kisao/KISAO#KISAO_0000610> \"2021-01-25\"^^xsd:date)\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000611> (<http://www.biomodels.net/kisao/KISAO#KISAO_0000611>)\n\n\n# Class: <http://www.biomodels.net/kisao/KISAO#KISAO_0000613> 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<http://www.biomodels.net/kisao/KISAO#KISAO_0000575>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000051> <http://www.biomodels.net/kisao/KISAO#KISAO_0000075> <http://www.biomodels.net/kisao/KISAO#KISAO_0000095> <http://www.biomodels.net/kisao/KISAO#KISAO_0000336> <http://www.biomodels.net/kisao/KISAO#KISAO_0000611> <http://www.biomodels.net/kisao/KISAO#KISAO_0000613> <http://www.biomodels.net/kisao/KISAO#KISAO_0000618> <http://www.biomodels.net/kisao/KISAO#KISAO_0000619>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> 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<http://www.biomodels.net/kisao/KISAO#KISAO_0000397> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> <http://www.biomodels.net/kisao/KISAO#KISAO_0000491>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000281> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> <http://www.biomodels.net/kisao/KISAO#KISAO_0000377> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> <http://www.biomodels.net/kisao/KISAO#KISAO_0000448> <http://www.biomodels.net/kisao/KISAO#KISAO_0000473>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000319> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000369> <http://www.biomodels.net/kisao/KISAO#KISAO_0000397> <http://www.biomodels.net/kisao/KISAO#KISAO_0000398> <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> <http://www.biomodels.net/kisao/KISAO#KISAO_0000408> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> <http://www.biomodels.net/kisao/KISAO#KISAO_0000448> <http://www.biomodels.net/kisao/KISAO#KISAO_0000473> <http://www.biomodels.net/kisao/KISAO#KISAO_0000491> <http://www.biomodels.net/kisao/KISAO#KISAO_0000497> <http://www.biomodels.net/kisao/KISAO#KISAO_0000499>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000056> <http://www.biomodels.net/kisao/KISAO#KISAO_0000094> <http://www.biomodels.net/kisao/KISAO#KISAO_0000273> <http://www.biomodels.net/kisao/KISAO#KISAO_0000306> <http://www.biomodels.net/kisao/KISAO#KISAO_0000314> <http://www.biomodels.net/kisao/KISAO#KISAO_0000363> <http://www.biomodels.net/kisao/KISAO#KISAO_0000407> <http://www.biomodels.net/kisao/KISAO#KISAO_0000419> <http://www.biomodels.net/kisao/KISAO#KISAO_0000433> <http://www.biomodels.net/kisao/KISAO#KISAO_0000470> <http://www.biomodels.net/kisao/KISAO#KISAO_0000473> <http://www.biomodels.net/kisao/KISAO#KISAO_0000491> <http://www.biomodels.net/kisao/KISAO#KISAO_0000497>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000064> <http://www.biomodels.net/kisao/KISAO#KISAO_0000261> <http://www.biomodels.net/kisao/KISAO#KISAO_0000286> <http://www.biomodels.net/kisao/KISAO#KISAO_0000380>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000071> <http://www.biomodels.net/kisao/KISAO#KISAO_0000088> <http://www.biomodels.net/kisao/KISAO#KISAO_0000089> <http://www.biomodels.net/kisao/KISAO#KISAO_0000090> <http://www.biomodels.net/kisao/KISAO#KISAO_0000091> <http://www.biomodels.net/kisao/KISAO#KISAO_0000093> <http://www.biomodels.net/kisao/KISAO#KISAO_0000232> <http://www.biomodels.net/kisao/KISAO#KISAO_0000233> <http://www.biomodels.net/kisao/KISAO#KISAO_0000234> <http://www.biomodels.net/kisao/KISAO#KISAO_0000560>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000086> <http://www.biomodels.net/kisao/KISAO#KISAO_0000087> <http://www.biomodels.net/kisao/KISAO#KISAO_0000321> <http://www.biomodels.net/kisao/KISAO#KISAO_0000434>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000231> <http://www.biomodels.net/kisao/KISAO#KISAO_0000317> <http://www.biomodels.net/kisao/KISAO#KISAO_0000320> <http://www.biomodels.net/kisao/KISAO#KISAO_0000365> <http://www.biomodels.net/kisao/KISAO#KISAO_0000447> <http://www.biomodels.net/kisao/KISAO#KISAO_0000468> <http://www.biomodels.net/kisao/KISAO#KISAO_0000499> <http://www.biomodels.net/kisao/KISAO#KISAO_0000575> <http://www.biomodels.net/kisao/KISAO#KISAO_0000595> <http://www.biomodels.net/kisao/KISAO#KISAO_0000598> <http://www.biomodels.net/kisao/KISAO#KISAO_0000599> <http://www.biomodels.net/kisao/KISAO#KISAO_0000600> <http://www.biomodels.net/kisao/KISAO#KISAO_0000617>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000241> <http://www.biomodels.net/kisao/KISAO#KISAO_0000274> <http://www.biomodels.net/kisao/KISAO#KISAO_0000278> <http://www.biomodels.net/kisao/KISAO#KISAO_0000573>)\nDisjointClasses(<http://www.biomodels.net/kisao/KISAO#KISAO_0000279> <http://www.biomodels.net/kisao/KISAO#KISAO_0000280> 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+name: Kinetic Simulation Algorithm Ontology (KiSAO)
+
+[Term]
+id: KISAO_0000000
+name: modelling and simulation algorithm
+property_value: altLabel "modeling and simulation algorithm" xsd:string
+property_value: definition "Algorithm used to instantiate a simulation from a mathematical model." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000003
+name: weighted stochastic simulation algorithm
+is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
+disjoint_from: KISAO_0000027 ! Gibson-Bruck next reaction algorithm
+property_value: altLabel "weighted SSA" xsd:string {comment="EXACT"}
+property_value: definition "The weighted stochastic simulation algorithm manipulates the probabilities measure of biochemical systems by sampling, in order to increase the fraction of simulation runs exhibiting rare events." xsd:string
+property_value: http://purl.org/dc/terms/creator "NLN" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/19045316" xsd:anyURI {comment="Kuwahara H, Mura I. (2008) An efficient and exact stochastic simulation method to analyse rare events in biochemical systems. J Chem Phys. 129(16):165101."}
+
+[Term]
+id: KISAO_0000015
+name: Gillespie first reaction algorithm
+is_a: KISAO_0000241 ! Gillespie-like method
+disjoint_from: KISAO_0000029 ! Gillespie direct algorithm
+property_value: altLabel "Gillespie's first reaction method" xsd:string {comment="EXACT"}
+property_value: definition "Stochastic simulation algorithm using the reaction probability density function (next-reaction density function), giving the probability that the next reaction will happen in a given time interval. To choose the next reaction to fire, the algorithm calculates a tentative reaction time for each reaction and then select the smallest." xsd:string
+property_value: http://purl.org/dc/terms/creator "NLN" xsd:string
+property_value: isImplementedIn "Cain" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1016/0021-9991(76)90041-3" xsd:anyURI {comment="Gillespie DT. A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions. Journal of Computational Physics, Volume 2 , pages 403-434 (1976)."}
+property_value: seeAlso "http://identifiers.org/doi/10.1021/j100540a008" xsd:anyURI {comment="Gillespie DT. Exact stochastic simulation of coupled chemical reactions. Journal of Physical Chemistry, Vol. 81, No. 25. (1977), pp. 2340-2361."}
+
+[Term]
+id: KISAO_0000017
+name: multi-state agent-based simulation method
+is_a: KISAO_0000363 ! rule-based simulation method
+disjoint_from: KISAO_0000021 ! StochSim nearest-neighbour algorithm
+property_value: altLabel "Morton-Firth" xsd:string {comment="EXACT"}
+property_value: definition "The agent-based simulation method instantiates each molecule as an individual software object. The interactions between those objects are determined by interaction probabilities according to experimental data. The probability is depended on the state the molecule is in at that specific time (molecules have multiple-state). Additionally, ''pseudo-molecules'' are introduced to the system in order to simulate unimolecular reactions. For simulation, continuous time is broken down into discrete, independent ''slices''. During each time slice one molecule is selected randomly, a second molecule or pseudo-molecule is selected afterwards (leading to either a unimolecular or a bimolecular reaction). The reaction will only take place if a produced random number exceeds the reaction probability calculated beforehand. In that case, the system is updated after that reaction." xsd:string
+property_value: isImplementedIn "StochSim" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/9628844" xsd:anyURI {comment="Morton-Firth, C.J, Bray, D. Predicting temporal fluctuations in an intracellular signalling pathway. Journal of Theoretical Biology, volume 192, pages 117-128 (1998)."}
+
+[Term]
+id: KISAO_0000019
+name: CVODE
+is_a: KISAO_0000433 ! CVODE-like method
+disjoint_from: KISAO_0000020 ! PVODE
+disjoint_from: KISAO_0000282 ! KINSOL
+disjoint_from: KISAO_0000282 ! KINSOL
+disjoint_from: KISAO_0000355 ! DASPK
+relationship: KISAO_0000359 KISAO_0000020 ! PVODE
+property_value: altLabel "code value ordinary differential equation solver" xsd:string {comment="EXACT"}
+property_value: altLabel "VODE" xsd:string {comment="RELATED"}
+property_value: altLabel "VODEPK" xsd:string {comment="RELATED"}
+property_value: definition "The CVODE is a package written in C that solves ODE initial value problems, in real N-space, written as y'=f(t,y),  y(t0)=y0. It is capable for stiff and non-stiff systems and uses two different linear multi-step methods, namely the Adam-Moulton [http://identifiers.org/biomodels.kisao/KISAO_0000280] method and the backward differentiation formula [http://identifiers.org/biomodels.kisao/KISAO_0000288]." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
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+property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/opencor" xsd:anyURI {comment="OpenCOR"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/pysces" xsd:anyURI {comment="PySCeS"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: isImplementedIn "libRoadRunner" xsd:string
+property_value: isImplementedIn "SBML-SAT" xsd:string
+property_value: isImplementedIn "SUNDIALS" xsd:string
+property_value: seeAlso "citeulike:1832863" xsd:anyURI {comment="Cohen S, Hindmarsh C. Cvode, A Stiff/nonstiff Ode Solver In C. Computers in Physics, Vol. 10 (2), pages 138-143 (1996)."}
+property_value: seeAlso "http://identifiers.org/doi/10.1145/1089014.1089020" xsd:anyURI {comment="Hindmarsh, A. C., et al., SUNDIALS: Suite of Nonlinear and Differential/Algebraic Equation Solvers, ACM Trans. Math. Softw., 31:363-396, 2005."}
+
+[Term]
+id: KISAO_0000020
+name: PVODE
+is_a: KISAO_0000433 ! CVODE-like method
+disjoint_from: KISAO_0000282 ! KINSOL
+disjoint_from: KISAO_0000283 ! IDA
+disjoint_from: KISAO_0000356 ! DASSL
+relationship: KISAO_0000359 KISAO_0000019 ! CVODE
+property_value: altLabel "parallel code value ordinary differential equation solver" xsd:string {comment="EXACT"}
+property_value: definition "PVODE is a general-purpose solver for ordinary differential equation (ODE) systems that implements methods for both stiff and nonstiff systems. [...] In the stiff case, PVODE uses a backward differentiation formula method [http://identifiers.org/biomodels.kisao/KISAO_0000288] combined with preconditioned GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000253] iteration. Parallelism is achieved by distributing the ODE solution vector into user-specified segments and parallelizing a set of vector kernels accordingly. For PDE-based ODE systems, we provide a module that generates a band block-diagonal preconditioner for use with the GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000253] iteration. PVODE is based on CVODE [http://identifiers.org/biomodels.kisao/KISAO_0000019]." xsd:string
+property_value: isImplementedIn "SUNDIALS" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1145/1089014.1089020" xsd:anyURI {comment="Hindmarsh, A. C., et al., SUNDIALS: Suite of Nonlinear and Differential/Algebraic Equation Solvers, ACM Trans. Math. Softw., 31:363-396, 2005."}
+property_value: seeAlso "http://identifiers.org/doi/10.1177/109434209901300405" xsd:anyURI {comment="Byrne GD, Hindmarsh AC. PVODE, an ODE Solver for Parallel Computers. International Journal of High Performance Computing Applications, Vol. 13 (4), pages 354-365 (1999)."}
+
+[Term]
+id: KISAO_0000021
+name: StochSim nearest-neighbour algorithm
+is_a: KISAO_0000363 ! rule-based simulation method
+relationship: KISAO_0000359 KISAO_0000264 ! cellular automata update method
+relationship: KISAO_0000360 KISAO_0000017 ! multi-state agent-based simulation method
+property_value: definition "The nearest-neighbour algorithm allows for the representation of spatial information, by adding a two-dimensional lattice in the form of a probabilistic cellular automata. That way, nearest neighbour interactions do additionally influence reactions taking place in the systems. Reactions between entities are calculated using the agent-based simulation algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000017]." xsd:string
+property_value: isImplementedIn "Stochsim 1.2 and more recent versions" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/11395441" xsd:anyURI {comment="Le Novere N, Shimizu TS. STOCHSIM: modelling of stochastic biomolecular processes. Bioinformatics, volume 17 (6), pages 575-576 (2001)."}
+
+[Term]
+id: KISAO_0000022
+name: Elf and Ehrenberg method
+is_a: KISAO_0000095 ! sub-volume stochastic reaction-diffusion algorithm
+disjoint_from: KISAO_0000076 ! Stundzia and Lumsden method
+relationship: KISAO_0000360 KISAO_0000027 ! Gibson-Bruck next reaction algorithm
+relationship: KISAO_0000360 KISAO_0000029 ! Gillespie direct algorithm
+property_value: altLabel "Elf algorithm" xsd:string {comment="EXACT"}
+property_value: altLabel "next-subvolume method" xsd:string {comment="EXACT"}
+property_value: altLabel "NSM" xsd:string {comment="EXACT"}
+property_value: definition "Sub-volume stochastic reaction-diffusion method that is a combination of the Direct Method [http://identifiers.org/biomodels.kisao/KISAO_0000029] for sampling the time for a next reaction or diffusion event in each subvolume, with Gibson and Bruck's Next Reaction Method [http://identifiers.org/biomodels.kisao/KISAO_0000027], which is used to keep track of in which subvolume an event occurs next. The subvolumes are kept sorted in a queue, implemented as a binary tree, according to increasing time of the next event. When an event has occurred in the subvolume at the top of the queue, new event times need to be sampled only for one (the event is a chemical reaction) or two (the event is a diffusion jump) subvolume(s)." xsd:string
+property_value: isImplementedIn "MesoRD" xsd:string
+property_value: isImplementedIn "SmartCell" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1049/sb:20045021" xsd:anyURI {comment="Elf J, Ehrenberg M. Spontaneous separation of bi-stable biochemical systems into spatial domains of opposite phases. Systems Biology, IEE Proceedings, volume 1 (2), pages 230-236 (2004)."}
+
+[Term]
+id: KISAO_0000027
+name: Gibson-Bruck next reaction algorithm
+is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
+relationship: KISAO_0000359 KISAO_0000015 ! Gillespie first reaction algorithm
+property_value: altLabel "Gibson and Bruck algorithm" xsd:string {comment="EXACT"}
+property_value: altLabel "Gibson-Bruck's next reaction algorithm" xsd:string {comment="EXACT"}
+property_value: altLabel "Gillespie-Gibson stochastic simulation algorithm" xsd:string {comment="EXACT"}
+property_value: altLabel "next reaction method" xsd:string {comment="EXACT"}
+property_value: altLabel "SSA-GB" xsd:string {comment="EXACT"}
+property_value: definition "As with the first reaction method [http://identifiers.org/biomodels.kisao/KISAO_0000015], a putative reaction time is calculated for each reaction, and the reaction with the shortest reaction time will be realized. However, the unused calculated reaction times are not wasted. The set of reactions is organized in a priority queue to allow for the efficient search for the fastest reaction. In addition, by using a so-called dependency graph only those reaction times are recalculated in each step, that are dependent on the reaction, which has been realized." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: isImplementedIn "Cain" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: isImplementedIn "SmartCell" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1021/jp993732q" xsd:anyURI {comment="Gibson MA, Bruck J. Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels. Journal of Physical Chemistry A, Vol. 104, pages 1876-1889 (2000)."}
+
+[Term]
+id: KISAO_0000028
+name: slow-scale stochastic simulation algorithm
+is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
+property_value: altLabel "slow-scale stochastic SSA" xsd:string {comment="EXACT"}
+property_value: altLabel "ssSSA" xsd:string {comment="EXACT"}
+property_value: definition "Attempt to overcome the problem of stiff systems by developing an ''approximate theory that allows one to stochastically advance the system in time by simulating the firings of only the slow reaction events''." xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/15638651" xsd:anyURI {comment="Cao Y, Gillespie DT, Petzold LR. The slow-scale stochastic simulation algorithm. Journal of Chemical Physics, Vol. 122, No. 1. (1 January 2005)."}
+
+[Term]
+id: KISAO_0000029
+name: Gillespie direct algorithm
+is_a: KISAO_0000241 ! Gillespie-like method
+relationship: KISAO_0000359 KISAO_0000051 ! Bortz-Kalos-Lebowitz algorithm
+property_value: altLabel "DM" xsd:string {comment="EXACT"}
+property_value: altLabel "Doob-Gillespie method" xsd:string {comment="EXACT"}
+property_value: altLabel "Gillespie's algorithm" xsd:string {comment="EXACT"}
+property_value: altLabel "Gillespie's direct method" xsd:string {comment="EXACT"}
+property_value: altLabel "SSA" xsd:string {comment="EXACT"}
+property_value: altLabel "stochastic simulation algorithm" xsd:string {comment="EXACT"}
+property_value: definition "Stochastic simulation algorithm using the reaction probability density function (next-reaction density function), giving the probability that the next reaction will happen in a given time interval. To choose the next reaction to fire, the algorithm directly and separately calculates the identity of the reaction and the time it will fire." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: isImplementedIn "BetaWB" xsd:string
+property_value: isImplementedIn "ByoDyn" xsd:string
+property_value: isImplementedIn "Cain" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/bionetgen" xsd:anyURI {comment="BioNetGen"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: seeAlso "http://identifiers.org/doi/10.1016/0021-9991(76)90041-3" xsd:anyURI {comment="Gillespie DT. A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions. Journal of Computational Physics, Volume 2 , pages 403-434 (1976)."}
+property_value: seeAlso "http://identifiers.org/doi/10.1021/j100540a008" xsd:anyURI {comment="Gillespie DT. Exact stochastic simulation of coupled chemical reactions. Journal of Physical Chemistry, Vol. 81, No. 25. (1977), pp. 2340-2361."}
+
+[Term]
+id: KISAO_0000030
+name: Euler forward method
+is_a: KISAO_0000261 ! Euler method
+disjoint_from: KISAO_0000031 ! Euler backward method
+property_value: altLabel "explicit Euler method" xsd:string {comment="EXACT"}
+property_value: altLabel "explicit Gaussian first order Runge-Kutta" xsd:string {comment="EXACT"}
+property_value: definition "The Euler method is an explicit one-step method for the numerical integration of ODES with a given initial value. The calculation of the next integration step at time t+1 is based on the state of the system at time point t." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: seeAlso "http://identifiers.org/isbn/052143064X" xsd:anyURI {comment="Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical Recipes. Cambridge University Press, New York, 2nd edition (1992)."}
+
+[Term]
+id: KISAO_0000031
+name: Euler backward method
+is_a: KISAO_0000261 ! Euler method
+property_value: altLabel "implicit Euler method" xsd:string {comment="EXACT"}
+property_value: altLabel "implicit Gaussian first order Runge-Kutta" xsd:string {comment="EXACT"}
+property_value: definition "The Euler backward method is an implicit one-step method for the numerical integration of ODES with a given initial value. The next state of a system is calculated by solving an equation that considers both, the current state of the system and the later one." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: isImplementedIn "GSL" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/052143064X" xsd:anyURI {comment="Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical Recipes in Fortran 77. Cambridge University Press (2001)."}
+
+[Term]
+id: KISAO_0000032
+name: explicit fourth-order Runge-Kutta method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+disjoint_from: KISAO_0000033 ! Rosenbrock method
+property_value: altLabel "ERK4" xsd:string {comment="EXACT"}
+property_value: altLabel "RK4" xsd:string {comment="EXACT"}
+property_value: altLabel "Runge-Kutta method" xsd:string {comment="EXACT"}
+property_value: definition "The Runge-Kutta method is a method for the numerical integration of ODES with a given initial value. The calculation of the next integration step at time t+1 is based on the state of the system at time point t, plus the product of the size of the interval and an estimated slope. The slope is a weighted average of 4 single slope points (beginning of interval-midpoint-midpoint-end of interval)." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: isImplementedIn "GSL" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: seeAlso "http://identifiers.org/isbn/0-471-91046-5 " xsd:anyURI {comment="Butcher JC. The Numerical Analysis of Ordinary Differential Equations: Runge-Kutta and General Linear Methods (1987). "}
+
+[Term]
+id: KISAO_0000033
+name: Rosenbrock method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: altLabel "generalized fourth order Runge-Kutta method" xsd:string {comment="EXACT"}
+property_value: altLabel "Kaps-Rentrop method" xsd:string {comment="EXACT"}
+property_value: definition "Some general implicit processes are given for the solution of simultaneous first-order differential equations. These processes, which use successive substitution, are implicit analogues of the (explicit) Runge-Kutta processes. They require the solution in each time step of one or more set of simultaneous linear equations, usually of a special and simple form. Processes of any required order can be devised, and they can be made to have a wide margin of stability when applied to a linear problem." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
+property_value: seeAlso "http://identifiers.org/doi/10.1093/comjnl/5.4.329" xsd:anyURI {comment="Rosenbrock HH. Some general implicit processes for the numerical solution of differential equations. The Computer Journal, pages 329-330 (1963)."}
+property_value: seeAlso "http://identifiers.org/isbn/052143064X" xsd:anyURI {comment="Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical Recipes. Cambridge University Press, New York, 2nd edition, pages 742-746 (1992)."}
+
+[Term]
+id: KISAO_0000038
+name: sorting stochastic simulation algorithm
+is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
+property_value: altLabel "sorting direct method" xsd:string {comment="EXACT"}
+property_value: altLabel "sorting SSA" xsd:string {comment="EXACT"}
+property_value: definition "In order to overcome the problem of high complexity of the stochastic simulation algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000029] when simulating large systems, the sorting direct method maintains a loosely sorted order of the reactions as the simulation executes." xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1016/j.compbiolchem.2005.10.007" xsd:anyURI {comment="McCollum J M, Peterson G D, Cox C D, Simpson M L, Samatova N F. The sorting direct method for stochastic simulation of biochemical systems with varying reaction execution behaviour. Computational Biology and Chemistry, Volume 30 (1), pages 39-49 (2006)."}
+
+[Term]
+id: KISAO_0000039
+name: tau-leaping method
+is_a: KISAO_0000621 ! stochastic simulation leaping method
+disjoint_from: KISAO_0000082 ! k-alpha leaping method
+property_value: altLabel "tauL" xsd:string {comment="EXACT"}
+property_value: definition "Approximate acceleration procedure of the stochastic simulation algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000029] that divides the time into subintervals and ''leaps'' from one to another, firing all the reaction events in each subinterval." xsd:string
+property_value: http://purl.org/dc/terms/creator "NLN" xsd:string
+property_value: isImplementedIn "ByoDyn" xsd:string
+property_value: isImplementedIn "Cain" xsd:string
+property_value: isImplementedIn "SmartCell" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1378322" xsd:anyURI {comment="Gillespie DT. Approximate accelerated stochastic simulation of chemically reacting systems. The Journal of Chemical Physics, Vol. 115 (4), pages 1716-1733 (2001). Section V."}
+
+[Term]
+id: KISAO_0000040
+name: Poisson tau-leaping method
+is_a: KISAO_0000039 ! tau-leaping method
+disjoint_from: KISAO_0000045 ! implicit tau-leaping method
+property_value: altLabel "explicit tau-leaping" xsd:string {comment="EXACT"}
+property_value: altLabel "explicit tau-leaping method with basic pre-leap check" xsd:string
+property_value: altLabel "explicit tau-leaping method with basic preleap check" xsd:string {comment="EXACT"}
+property_value: altLabel "poisson tau-leaping" xsd:string {comment="EXACT"}
+property_value: definition "Explicit tau-leaping method with basic pre leap check." xsd:string
+property_value: isImplementedIn "ByoDyn" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1378322" xsd:anyURI {comment="Gillespie DT. Approximate accelerated stochastic simulation of chemically reacting systems. The Journal of Chemical Physics, Vol. 115 (4), pages 1716-1733 (2001). Section V."}
+
+[Term]
+id: KISAO_0000045
+name: implicit tau-leaping method
+is_a: KISAO_0000039 ! tau-leaping method
+property_value: definition "Contrary to the explicit tau-leaping [http://identifiers.org/biomodels.kisao/KISAO_0000039 and http://identifiers.org/biomodels.kisao/KISAO_0000245 some http://identifiers.org/biomodels.kisao/KISAO_0000239] , the implicit tau-leaping allows for much larger time-steps when simulating stiff systems." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1627296" xsd:anyURI {comment="Rathinam M, Petzold L R, Cao Y, Gillespie D T. Stiffness in stochastic chemically reacting systems: The implicit tau-leaping method. The Journal of Chemical Physics, Volume 119 (24), pages 12784-12794 (2003)."}
+
+[Term]
+id: KISAO_0000046
+name: trapezoidal tau-leaping method
+is_a: KISAO_0000039 ! tau-leaping method
+property_value: altLabel "trapezoidal implicit tau-leaping method" xsd:string {comment="EXACT"}
+property_value: definition "Formula for accelerated discrete efficient stochastic simulation of chemically reacting system [which] has better accuracy and stiff stability properties than the explicit and implicit [http://identifiers.org/biomodels.kisao/KISAO_0000045] tau-leaping formulas for discrete stochastic systems, and it limits to the trapezoidal rule in the deterministic regime." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: seeAlso "citeulike:1755561" xsd:anyURI {comment="Cao Y, Petzold L. Trapezoidal tau-leaping formula for the stochastic simulation of biochemical systems. Foundations of Systems Biology in Engineering (FOSBE), pages 149-152 (2005)."}
+
+[Term]
+id: KISAO_0000048
+name: adaptive explicit-implicit tau-leaping method
+is_a: KISAO_0000039 ! tau-leaping method
+property_value: definition "Modification of the original tau-selection strategy [http://identifiers.org/biomodels.kisao/KISAO_0000040], designed for explicit tau-leaping, is modified to apply to implicit tau-leaping, allowing for longer steps when the system is stiff. Further, an adaptive strategy is proposed that identifies stiffness and automatically chooses between the explicit and the (new) implicit tau-selection methods to achieve better efficiency." xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2745299" xsd:anyURI {comment="Cao Y, Gillespie DT, Petzold LR. Adaptive explicit-implicit tau-leaping method with automatic tau selection. The Journal of Chemical Physics, Vol. 126 (22) (2007)."}
+
+[Term]
+id: KISAO_0000051
+name: Bortz-Kalos-Lebowitz algorithm
+is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
+disjoint_from: KISAO_0000075 ! Gillespie multi-particle method
+relationship: KISAO_0000359 KISAO_0000029 ! Gillespie direct algorithm
+property_value: altLabel "BKL" xsd:string {comment="EXACT"}
+property_value: altLabel "DMC" xsd:string {comment="EXACT"}
+property_value: altLabel "dynamic Monte Carlo" xsd:string {comment="EXACT"}
+property_value: altLabel "dynamic Monte Carlo method" xsd:string {comment="EXACT"}
+property_value: altLabel "kinetic Monte Carlo" xsd:string {comment="EXACT"}
+property_value: altLabel "kinetic Monte Carlo method" xsd:string {comment="EXACT"}
+property_value: altLabel "KMC" xsd:string {comment="EXACT"}
+property_value: altLabel "n-fold way" xsd:string {comment="EXACT"}
+property_value: definition "The Bortz-Kalos-Lebowitz (or: kinetic Monte-Carlo-) method is a stochastic method for the simulation of time evolution of processes using (pseudo-)random numbers." xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1016/0021-9991(75)90060-1" xsd:anyURI {comment="Bortz AB, Kalos MH, Lebowitz JL. A new algorithm for Monte Carlo simulation of Ising spin systems. Journal of Computational Physics, Vol. 17 (1), pages 10-18 (1975)."}
+
+[Term]
+id: KISAO_0000056
+name: Smoluchowski equation based method
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+disjoint_from: KISAO_0000094 ! Livermore solver
+disjoint_from: KISAO_0000094 ! Livermore solver
+disjoint_from: KISAO_0000094 ! Livermore solver
+disjoint_from: KISAO_0000094 ! Livermore solver
+disjoint_from: KISAO_0000094 ! Livermore solver
+disjoint_from: KISAO_0000094 ! Livermore solver
+property_value: definition "Method based on the Smoluchowski equation." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "urn:issn:0942-9352" xsd:anyURI {comment="Smoluchowski M. Mathematical theory of the kinetics of the coagulation of colloidal solutions. Z. Phys. Chem, Vol. 92, No. 129. (1917)."}
+
+[Term]
+id: KISAO_0000057
+name: Brownian diffusion Smoluchowski method
+is_a: KISAO_0000056 ! Smoluchowski equation based method
+disjoint_from: KISAO_0000058 ! Greens function reaction dynamics
+property_value: definition "In the Brownian diffusion Smoluchowski method, ''each molecule is treated as a point-like particle that diffuses freely in three-dimensional space. When a pair of reactive molecules collide, such as an enzyme and its substrate, a reaction occurs and the simulated reactants are replaced by products. [..] Analytic solutions are presented for some simulation parameters while others are calculated using look-up tables''. Supported chemical processes include molecular diffusion, treatment of surfaces, zeroth-order-, unimolecular-, and bimolecular reactions." xsd:string
+property_value: isImplementedIn "Smoldyn" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/16204833" xsd:anyURI {comment="Andrews SS, Bray D. Stochastic simulation of chemical reactions with spatial resolution and single molecule detail. Phys Biol, volume 1 (3-4), pages 137-151 (December 2004)."}
+
+[Term]
+id: KISAO_0000058
+name: Greens function reaction dynamics
+is_a: KISAO_0000056 ! Smoluchowski equation based method
+property_value: altLabel "GFRD" xsd:string {comment="EXACT"}
+property_value: altLabel "Green's function reaction dynamics" xsd:string {comment="EXACT"}
+property_value: definition "Method that simulates biochemical networks on particle level. It considers both changes in time and space by ''exploiting both the exact solution of the Smoluchowski Equation to set up an event-driven algorithm'' which allows for large jumps in time when the considered particles are far away from each other [in space] and thus cannot react. GFRD combines the propagation of particles in space with the reactions taking place between them in one simulation step." xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2137716" xsd:anyURI {comment="Van Zon JS, Ten Wolde PR. Green's-function reaction dynamics: A particle-based approach for simulating biochemical networks in time and space. Journal of Chemical Physics, Volume 123 (23) (2005)."}
+
+[Term]
+id: KISAO_0000064
+name: Runge-Kutta based method
+is_a: KISAO_0000377 ! one-step method
+disjoint_from: KISAO_0000261 ! Euler method
+relationship: KISAO_0000361 KISAO_0000261 ! Euler method
+property_value: altLabel "modified Euler method" xsd:string {comment="RELATED"}
+property_value: definition "A method of numerically integrating ordinary differential equations, which uses a sampling of slopes through an interval and takes a weighted average to determine the right end point. This averaging gives a very accurate approximation." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: isImplementedIn "ByoDyn" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://identifiers.org/isbn/0-471-91046-5" xsd:anyURI {comment="Butcher JC. The Numerical Analysis of Ordinary Differential Equations: Runge-Kutta and General Linear Methods (1987)."}
+
+[Term]
+id: KISAO_0000068
+name: deterministic cellular automata update algorithm
+is_a: KISAO_0000264 ! cellular automata update method
+property_value: definition "A cellular automaton is a discrete model of a regular grid of cells with a finite number of dimensions. Each cell has a finite number of defined states. The automaton changes its state in a discrete manner, meaning that the state of a cell at time t is determined by a function of the states of its neighbours at time t - 1. These neighbours are a selection of cells relative to the specified cell. Famous examples for deterministic cellular automata are Conway's game of life or Wolfram's elementary cellular automata." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-0252000232" xsd:anyURI {comment="Burks, Arthur W (Editor). Essays on Cellular Automata. University of Illinois Press (1970)."}
+
+[Term]
+id: KISAO_0000071
+name: LSODE
+is_a: KISAO_0000094 ! Livermore solver
+disjoint_from: KISAO_0000088 ! LSODA
+relationship: KISAO_0000360 KISAO_0000288 ! backward differentiation formula
+relationship: KISAO_0000360 KISAO_0000364 ! Adams predictor-corrector method
+property_value: altLabel "Livermore solver for ordinary differential equations" xsd:string {comment="EXACT"}
+property_value: definition "LSODE solves stiff and nonstiff systems of the form dy/dt = f. In the stiff case, it treats the Jacobian matrix sf/dy as either a dense (full) or a banded matrix, and as either user-supplied or internally approximated by difference quotients. It uses Adams methods (predictor-corrector) [http://identifiers.org/biomodels.kisao/KISAO_0000364] in the nonstiff case, and Backward Differentiation Formula (BDF) methods (the Gear methods) [http://identifiers.org/biomodels.kisao/KISAO_0000288] in the stiff case." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: seeAlso "citeulike:1774586" xsd:anyURI {comment="Radhakrishnan K, Hindmarsh AC. Description and Use of LSODE, the Livermore Solver for Ordinary Differential Equations. Lawrence Livermore National Laboratory Report, Vol. UCRL-ID-113855 (1993)."}
+property_value: seeAlso "http://identifiers.org/doi/10.1145/1218052.1218054" xsd:anyURI {comment="Hindmarsh AC. LSODE and LSODI, two new initial value ordinary differential equation solvers. SIGNUM Newsletter, Volume 15 (4), pages 10-11 (1980)."}
+
+[Term]
+id: KISAO_0000074
+name: binomial tau-leaping method
+is_a: KISAO_0000039 ! tau-leaping method
+relationship: KISAO_0000359 KISAO_0000095 ! sub-volume stochastic reaction-diffusion algorithm
+property_value: altLabel "binomial tau-leap spatial stochastic simulation algorithm" xsd:string {comment="EXACT"}
+property_value: altLabel "BtauL" xsd:string {comment="EXACT"}
+property_value: definition "Coarse grained modified version of the next subvolume method [http://identifiers.org/biomodels.kisao/KISAO_0000022] that allows the user to consider both diffusion and reaction events in relatively long simulation time spans as compared with the original method and other commonly used fully stochastic computational methods." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2771548" xsd:anyURI {comment="Marquez-Lago T., Burrage K. Binomial tau-leap spatial stochastic simulation algorithm for applications in chemical kinetics. The Journal of Chemical Physics, Vol. 127 (10) (2007)."}
+
+[Term]
+id: KISAO_0000075
+name: Gillespie multi-particle method
+is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
+relationship: KISAO_0000360 KISAO_0000029 ! Gillespie direct algorithm
+relationship: KISAO_0000360 KISAO_0000334 ! multiparticle lattice gas automata
+property_value: altLabel "Gillespie's multi-particle method" xsd:string {comment="EXACT"}
+property_value: altLabel "GMP" xsd:string {comment="EXACT"}
+property_value: altLabel "particle-based spatial stochastic method" xsd:string {comment="EXACT"}
+property_value: definition "Combination of the multiparticle method for diffusion [http://identifiers.org/biomodels.kisao/KISAO_0000334] and the SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029]." xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/16731694" xsd:anyURI {comment="Rodriguez VJ, Kaandorp JA, Dobrzynski M, Blom JG. Spatial stochastic modelling of the phosphoenolpyruvate-dependent phosphotransferase (PTS) pathway in Escherichia coli. Bioinformatics, Vol. 22 (15), pages 1895-1901 (2006)."}
+
+[Term]
+id: KISAO_0000076
+name: Stundzia and Lumsden method
+is_a: KISAO_0000095 ! sub-volume stochastic reaction-diffusion algorithm
+property_value: altLabel "RD SSA" xsd:string {comment="EXACT"}
+property_value: altLabel "reaction-diffusion stochastic simulation algorithm" xsd:string {comment="EXACT"}
+property_value: definition "Sub-volume stochastic reaction-diffusion method that using Green's function to link the bulk diffusion coefficient D in Fick's differential law to the corresponding transition rate probability for diffusion of a particle between finite volume elements. This generalized stochastic algorithm enables to numerically calculate the time evolution of a spatially inhomogeneous mixture of reaction-diffusion species in a finite volume. The time step is stochastic and is generated by a probability distribution determined by the intrinsic reaction kinetics and diffusion dynamics." xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1006/jcph.1996.0168" xsd:anyURI {comment="Stundzia AB, Lumsden CJ. Stochastic simulation of coupled reaction-diffusion processes. J Comput Phys, Vol. 127 (1), pages 196-207 (1996)."}
+
+[Term]
+id: KISAO_0000081
+name: estimated midpoint tau-leaping method
+is_a: KISAO_0000039 ! tau-leaping method
+property_value: altLabel "explicit tau-leaping method with estimated-mid point technique" xsd:string {comment="EXACT"}
+property_value: definition "Estimated-Midpoint tau-Leap Method: For the selected leaping time tau which satisfies the Leap Condition, compute the expected state change lambda' = tau sumj( aj(x)vj ) during [t, t + tau). Then, with x' =x + [lambda'/2], generate for each j = 1,...,M a sample value kj of the Poisson random variable P(aj(x'), tau). Compute the actual state change, lambda = sumj( kjvj ), and effect the leap by replacing t by t + tau and x by x + lambda." xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1378322" xsd:anyURI {comment="Gillespie DT. Approximate accelerated stochastic simulation of chemically reacting systems. The Journal of Chemical Physics, Vol. 115 (4), pages 1716-1733 (2001). Section VI."}
+
+[Term]
+id: KISAO_0000082
+name: k-alpha leaping method
+is_a: KISAO_0000621 ! stochastic simulation leaping method
+relationship: KISAO_0000359 KISAO_0000039 ! tau-leaping method
+property_value: definition "Alternative to the tau-leaping [http://identifiers.org/biomodels.kisao/KISAO_0000039], where one leaps a fixed number of reaction-events." xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1378322" xsd:anyURI {comment="Gillespie DT. Approximate accelerated stochastic simulation of chemically reacting systems. The Journal of Chemical Physics, Vol. 115 (4), pages 1716-1733 (2001). Section VIII."}
+
+[Term]
+id: KISAO_0000084
+name: nonnegative Poisson tau-leaping method
+is_a: KISAO_0000039 ! tau-leaping method
+relationship: KISAO_0000359 KISAO_0000040 ! Poisson tau-leaping method
+property_value: altLabel "modified poisson tau-leaping" xsd:string
+property_value: definition "The explicit tau-leaping procedure attempts to speed up the stochastic simulation of a chemically reacting system by approximating the number of firings of each reaction channel during a chosen time increment Tau as a Poisson random variable. Since the Poisson random variable can have arbitrarily large sample values, there is always the possibility that this procedure will cause one or more reaction channels to fire so many times during Tau that the population of some reactant species will be driven negative. Two recent papers have shown how that unacceptable occurrence can be avoided by replacing the Poisson random variables with binomial random variables, whose values are naturally bounded. This paper describes a modified Poisson tau-leaping procedure that also avoids negative populations, but is easier to implement than the binomial procedure. The new Poisson procedure also introduces a second control parameter, whose value essentially dials the procedure from the original Poisson tau-leaping at one extreme to the exact stochastic simulation algorithm at the other; therefore, the modified Poisson procedure will generally be more accurate than the original Poisson procedure [http://identifiers.org/biomodels.kisao/KISAO_0000040]." xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1992473" xsd:anyURI {comment="Cao Y, Gillespie DT, Petzold LR. Avoiding negative populations in explicit Poisson tau-leaping. Journal of Chemical Physics, Vol. 123, 4104 (2005)."}
+
+[Term]
+id: KISAO_0000086
+name: Fehlberg method
+is_a: KISAO_0000435 ! embedded Runge-Kutta 5(4) method
+disjoint_from: KISAO_0000087 ! Dormand-Prince method
+property_value: altLabel "RKF45" xsd:string {comment="EXACT"}
+property_value: altLabel "Runge-Kutta-Fehlberg method" xsd:string {comment="EXACT"}
+property_value: definition "The method was developed by the German mathematician Erwin Fehlberg and is based on the class of Runge-Kutta methods. The Runge-Kutta-Fehlberg method uses an O(h4) method together with an O(h5) method that uses all of the points of the O(h4) method, and hence is often referred to as an RKF45 method. Similar schemes with different orders have since been developed. By performing one extra calculation that would be required for an RK5 method, the error in the solution can be estimated and controlled and an appropriate step size can be determined automatically, making this method efficient for ordinary problems of automated numerical integration of ordinary differential equations." xsd:string
+property_value: isImplementedIn "GSL" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: seeAlso "http://identifiers.org/doi/10.1007/BF02241732" xsd:anyURI {comment="Erwin Fehlberg (1970). Klassische Runge-Kutta-Formeln vierter und niedrigerer Ordnung mit Schrittweiten-Kontrolle und ihre Anwendung auf Wärmeleitungsprobleme, Computing (Arch. Elektron. Rechnen), vol. 6, pp. 61-71."}
+property_value: seeAlso "http://identifiers.org/pubmed/14990450" xsd:anyURI {comment="Takahashi K, Kaizu K, Hu B, Tomita M. A multi-algorithm, multi-timescale method for cell simulation. Bioinformatics volume 20(4), pages 538-46 (2004)."}
+
+[Term]
+id: KISAO_0000087
+name: Dormand-Prince method
+is_a: KISAO_0000435 ! embedded Runge-Kutta 5(4) method
+property_value: altLabel "DOPRI" xsd:string
+property_value: altLabel "Prince-Dormand method" xsd:string {comment="EXACT"}
+property_value: definition "Dormand-Prince is an explicit method for the numerical integration of ODES with a given initial value.\nIt is an 'embedded Runge-Kutta method' [http://identifiers.org/biomodels.kisao/KISAO_0000302] RK5 (4) which (a) has a 'small' principal truncation term in the Fifth order and (b) has an extended region of absolute stability." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: isImplementedIn "ECell3" xsd:string
+property_value: isImplementedIn "GSL" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: isImplementedIn "Matlab" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1016/0771-050X(80)90013-3" xsd:anyURI {comment="Dormand J, Prince P. A family of embedded Runge-Kutta formulae. Journal of Computational and Applied Mathematics, Volume 6, pages 19-26 (1980)."}
+property_value: seeAlso "http://identifiers.org/pubmed/14990450" xsd:anyURI {comment="Takahashi K, Kaizu K, Hu B, Tomita M. A multi-algorithm, multi-timescale method for cell simulation. Bioinformatics volume 20(4), pages 538-46 (2004)."}
+
+[Term]
+id: KISAO_0000088
+name: LSODA
+is_a: KISAO_0000094 ! Livermore solver
+relationship: KISAO_0000359 KISAO_0000071 ! LSODE
+relationship: KISAO_0000360 KISAO_0000288 ! backward differentiation formula
+relationship: KISAO_0000360 KISAO_0000289 ! Adams method
+property_value: altLabel "Livermore solver for ordinary differential equations with automatic method switching" xsd:string {comment="EXACT"}
+property_value: definition "LSODA solves systems dy/dt = f with a dense or banded Jacobian when the problem is stiff, but it automatically selects between non-stiff (Adams [http://identifiers.org/biomodels.kisao/KISAO_0000289]) and stiff (BDF [http://identifiers.org/biomodels.kisao/KISAO_0000288]) methods. It uses the non-stiff method initially, and dynamically monitors data in order to decide which method to use." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0904010" xsd:anyURI {comment="Petzold LR. Automatic Selection of Methods for Solving Stiff and Nonstiff Systems of Ordinary Differential Equations. SIAM Journal on Scientific and Statistical Computing, Vol. 4 (1), pages 136-148 (1983)."}
+property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
+property_value: seeAlso "http://www.nea.fr/abs/html/uscd1227.html" xsd:anyURI {comment="Petzold LR, Hindmarsh, AC. LSODAR: Livermore solver of ordinary differential equations with automatic method switching and root finding, Computing and Mathematics Research Division, 1-316 Lawerence Livermore National Laboratory (1987)."}
+
+[Term]
+id: KISAO_0000089
+name: LSODAR
+is_a: KISAO_0000094 ! Livermore solver
+relationship: KISAO_0000359 KISAO_0000088 ! LSODA
+property_value: altLabel "Livermore solver for ordinary differential equations with automatic method switching and root finding" xsd:string {comment="EXACT"}
+property_value: altLabel "ordinary differential equation solver for stiff or non-stiff systems with root finding" xsd:string {comment="EXACT"}
+property_value: definition "LSODAR is a variant of LSODA [http://identifiers.org/biomodels.kisao/KISAO_0000088] with a root finding capability added. Thus it solves problems dy/dt = f with dense or banded Jacobian and automatic method selection, and at the same time, it finds the roots of any of a set of given functions of the form g(t,y). This is often useful for finding stop conditions, or for finding points at which a switch is to be made in the function f." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
+property_value: seeAlso "http://www.nea.fr/abs/html/uscd1228.html" xsd:anyURI {comment="Petzold LR, Hindmarsh, AC. LSODAR: Livermore solver of ordinary differential equations with automatic method switching and root finding, Computing and Mathematics Research Division, 1-316 Lawerence Livermore National Laboratory (1987)."}
+
+[Term]
+id: KISAO_0000090
+name: LSODI
+is_a: KISAO_0000094 ! Livermore solver
+relationship: KISAO_0000359 KISAO_0000071 ! LSODE
+property_value: altLabel "Livermore solver for ordinary differential equations, implicit version" xsd:string {comment="EXACT"}
+property_value: definition "LSODI solves systems given in linearly implicit form, including differential-algebraic systems." xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1145/1218052.1218054" xsd:anyURI {comment="Hindmarsh AC. LSODE and LSODI, two new initial value ordinary differential equation solvers. SIGNUM Newsletter, Volume 15 (4), pages 10-11 (1980)."}
+property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
+
+[Term]
+id: KISAO_0000091
+name: LSODIS
+is_a: KISAO_0000094 ! Livermore solver
+relationship: KISAO_0000359 KISAO_0000071 ! LSODE
+property_value: altLabel "Livermore solver for ordinary differential equations, implicit sparse version" xsd:string {comment="EXACT"}
+property_value: definition "LSODIS is a set of general-purpose FORTRAN routines solver for the initial value problem for ordinary differential equation systems. It is suitable for both stiff and nonstiff systems. LSODIS treat systems in the linearly implicit form A(t,y) dy/dt = g(t,y), A = a square matrix, i.e. with the derivative dy/dt implicit, but linearly so." xsd:string
+property_value: http://purl.org/dc/terms/creator "dk" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
+property_value: seeAlso "http://www.nea.fr/abs/html/uscd1225.html" xsd:anyURI {comment="Seager M, Balsdon S. LSODIS - A sparse implicit ODE solver. 10th World Congress on System Simulation and Scientific Computation, pages 437-439 (1983)."}
+
+[Term]
+id: KISAO_0000093
+name: LSODPK
+is_a: KISAO_0000094 ! Livermore solver
+relationship: KISAO_0000359 KISAO_0000071 ! LSODE
+relationship: KISAO_0000360 KISAO_0000354 ! Krylov subspace projection method
+property_value: altLabel "Livermore solver for ordinary differential equations for stiff and nonstiff systems with krylov corrector iteration" xsd:string {comment="EXACT"}
+property_value: definition "LSODPK is a set of FORTRAN subroutines for solving the initial value problem for stiff and nonstiff systems of ordinary differential equations. In solving stiff systems, LSODPK uses a corrector iteration composed of Newton iteration and one of four preconditioned Krylov subspace iteration methods [http://identifiers.org/biomodels.kisao/KISAO_0000354]. The user must select the desired Krylov method and supply a pair of routine to evaluate, preprocess, and solve the (left and/or right) preconditioner matrices. Aside from preconditioning, the implementation is matrix-free, meaning that explicit storage of the Jacobian (or related) matrix is not required. The method is experimental because the scope of problems for which it is effective is not well-known, and users are forewarned that LSODPK may or may not be competitive with traditional methods on a given problem. LSODPK also includes an option for a user-supplied linear system solver to be used without Krylov iteration." xsd:string
+property_value: http://purl.org/dc/terms/creator "NLN" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
+
+[Term]
+id: KISAO_0000094
+name: Livermore solver
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: definition "Method to solve ordinary differential equations developed at the Lawrence Livermore National Laboratory." xsd:string
+property_value: http://purl.org/dc/terms/creator "NLN" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000095
+name: sub-volume stochastic reaction-diffusion algorithm
+is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
+disjoint_from: KISAO_0000336 ! D-leaping method
+property_value: definition "Stochastic method using a combination of discretisation of compartment volumes into voxels and Gillespie-like algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000241] to simulate the evolution of the system." xsd:string
+property_value: http://purl.org/dc/terms/creator "NLN" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000231
+name: Pahle hybrid method
+is_a: KISAO_0000352 ! hybrid method
+disjoint_from: KISAO_0000317 ! E-Cell multi-algorithm simulation method
+relationship: KISAO_0000246 KISAO_0000027 ! Gibson-Bruck next reaction algorithm
+property_value: definition "The hybrid method combines the stochastic 'Gibson-Bruck's next reaction method' [http://identifiers.org/biomodels.kisao/KISAO_0000027] with different algorithms for the numerical integration of ODEs [http://identifiers.org/biomodels.kisao/KISAO_0000245 some http://identifiers.org/biomodels.kisao/KISAO_0000374]. The biochemical network is dynamically partitioned into a deterministic and a stochastic subnet depending on the current particle numbers in the system. The user can define limits for when a particle number should be considered low or high. The stochastic subnet contains reactions involving low numbered species as substrate or product. All the other reactions form the deterministic subnet. The two subnets are then simulated in parallel using the stochastic and deterministic solver, respectively. The reaction probabilities in the stochastic subnet are approximated as constant between two stochastic reaction events." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://identifiers.org/doi/10.1093/bioinformatics/btl485" xsd:anyURI {comment="COPASI--a COmplex PAthway SImulator. Hoops S, Sahle S, Gauges R, Lee C, Pahle J, Simus N, Singhal M, Xu L, Mendes P, Kummer U. Bioinformatics. 2006 Dec 15;22(24):3067-74. Epub 2006 Oct 10."}
+
+[Term]
+id: KISAO_0000232
+name: LSOIBT
+is_a: KISAO_0000094 ! Livermore solver
+relationship: KISAO_0000359 KISAO_0000071 ! LSODE
+property_value: altLabel "Livermore solver for ordinary differential equations given in implicit form, with block-tridiagonal Jacobian treatment" xsd:string {comment="EXACT"}
+property_value: definition "LSOIBT solves linearly implicit systems in which the matrices involved are all assumed to be block-tridiagonal. Linear systems are solved by the LU method." xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
+
+[Term]
+id: KISAO_0000233
+name: LSODES
+is_a: KISAO_0000094 ! Livermore solver
+relationship: KISAO_0000359 KISAO_0000071 ! LSODE
+property_value: altLabel "Livermore solver for ordinary differential equations with general sparse Jacobian matrix" xsd:string {comment="EXACT"}
+property_value: definition "LSODES solves systems dy/dt = f and in the stiff case treats the Jacobian matrix in general sparse form. It determines the sparsity structure on its own, or optionally accepts this information from the user. It then uses parts of the Yale Sparse Matrix Package (YSMP) to solve the linear systems that arise, by a sparse (direct) LU factorization/backsolve method." xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
+
+[Term]
+id: KISAO_0000234
+name: LSODKR
+is_a: KISAO_0000094 ! Livermore solver
+relationship: KISAO_0000359 KISAO_0000071 ! LSODE
+relationship: KISAO_0000359 KISAO_0000093 ! LSODPK
+relationship: KISAO_0000360 KISAO_0000354 ! Krylov subspace projection method
+property_value: altLabel "Livermore solver for ordinary differential equations, with preconditioned Krylov iteration methods for the Newton correction linear systems, and with root finding." xsd:string {comment="EXACT"}
+property_value: definition "LSODKR is an initial value ODE solver for stiff and nonstiff systems. It is a variant of the LSODPK [http://identifiers.org/biomodels.kisao/KISAO_0000093] and LSODE [http://identifiers.org/biomodels.kisao/KISAO_0000071] solvers, intended mainly for large stiff systems. The main differences between LSODKR and LSODE [http://identifiers.org/biomodels.kisao/KISAO_0000071] are the following: a) for stiff systems, LSODKR uses a corrector iteration composed of Newton iteration and one of four preconditioned Krylov subspace iteration methods. The user must supply routines for the preconditioning operations, b) within the corrector iteration, LSODKR does automatic switching between functional (fixpoint) iteration and modified Newton iteration, c) LSODKR includes the ability to find roots of given functions of the solution during the integration." xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-0444866073" xsd:anyURI {comment="A. C. Hindmarsh, ODEPACK, A Systematized Collection of ODE Solvers, in Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, 1983 (vol. 1 of IMACS Transactions on Scientific Computation), pp. 55-64."}
+
+[Term]
+id: KISAO_0000241
+name: Gillespie-like method
+is_a: KISAO_0000319 ! Monte Carlo method
+disjoint_from: KISAO_0000274 ! first-passage Monte Carlo algorithm
+property_value: definition "Stochastic simulation algorithm using an approach alike the one described in Gillespie's papers of 1976 and 1977." xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000261
+name: Euler method
+is_a: KISAO_0000377 ! one-step method
+property_value: definition "The Euler method, named after Leonhard Euler, is a first-order numerical procedure for solving ordinary differential equations (ODEs) with a given initial value." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "ByoDyn" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: seeAlso "http://identifiers.org/isbn/052143064X" xsd:anyURI {comment="Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical Recipes in Fortran 77. Cambridge University Press (2001)."}
+
+[Term]
+id: KISAO_0000263
+name: NFSim agent-based simulation method
+is_a: KISAO_0000017 ! multi-state agent-based simulation method
+disjoint_from: KISAO_0000362 ! implicit-state Doob-Gillespie algorithm
+relationship: KISAO_0000361 KISAO_0000029 ! Gillespie direct algorithm
+property_value: definition "A generalization a rule-based version of 'Gillespie's direct method' (SSA) [http://identifiers.org/biomodels.kisao/KISAO_0000029]. The method is guaranteed to produce the same results as the exact SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] by cycling over three primary steps. First, NFsim calculates the probability or propensity for each rule to take effect given the current molecular states. Second, it samples the time to the next reaction event and selects the corresponding reaction rule. Finally, NFsim executes the selected reaction by applying the rule and updating the molecular agents accordingly." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/bionetgen" xsd:anyURI {comment="NFSim"}
+property_value: seeAlso "http://identifiers.org/doi/10.1038/nmeth.1546" xsd:anyURI {comment="Sneddon MW, Faeder JR and Emonet T. Efficient modelling, simulation and coarse-graining of biological complexity with NFsim. Nature Methods (2011) 8(2):177-83."}
+
+[Term]
+id: KISAO_0000264
+name: cellular automata update method
+is_a: KISAO_0000363 ! rule-based simulation method
+property_value: altLabel "CA" xsd:string {comment="EXACT"}
+property_value: altLabel "cellular automata" xsd:string {comment="EXACT"}
+property_value: altLabel "cellular spaces" xsd:string {comment="EXACT"}
+property_value: altLabel "cellular structures" xsd:string {comment="EXACT"}
+property_value: altLabel "homogeneous structures" xsd:string {comment="EXACT"}
+property_value: altLabel "iterative arrays" xsd:string {comment="EXACT"}
+property_value: altLabel "tessellation automata" xsd:string {comment="EXACT"}
+property_value: altLabel "tessellation structures" xsd:string {comment="EXACT"}
+property_value: definition "Cellular automata are mathematical idealizations of physical systems in which space and time are discrete, and physical quantities take on a finite set of discrete values. A cellular automaton consists of a regular uniform lattice (or ''array''), usually infinite in extent, with a discrete variable at each site (''cell''). A cellular automaton evolves in discrete time steps, with the value of the variable at one site being affected by the values of variables at sites in its ''neighbourhood'' on the previous time step. The neighbourhood of a site is typically taken to be the site itself and all immediately adjacent sites. The variables at each site are updated simultaneously (''synchronously''), based on the values of the variables in their neighbourhood at the preceding time step, and according to a definite set of ''local rules''." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1103/RevModPhys.55.601" xsd:anyURI {comment="Wolfram, Stephen (1983) Statistical mechanics of cellular automata. Reviews of Modern Physics 55 (3): 601-644."}
+
+[Term]
+id: KISAO_0000273
+name: hard-particle molecular dynamics
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: definition "A collision-driven molecular dynamics algorithm for a system of non-spherical particles." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1016/j.jcp.2004.08.014" xsd:anyURI {comment="Aleksandar Donev, Salvatore Torquato, Frank H. Stillinger, Neighbor list collision-driven molecular dynamics simulation for nonspherical hard particles. I. Algorithmic details, Journal of Computational Physics, v.202 n.2, p.737-764, 20 January 2005"}
+
+[Term]
+id: KISAO_0000274
+name: first-passage Monte Carlo algorithm
+is_a: KISAO_0000319 ! Monte Carlo method
+property_value: altLabel "AED diffusion kinetic Monte Carlo method" xsd:string {comment="EXACT"}
+property_value: altLabel "AED DKMC" xsd:string {comment="EXACT"}
+property_value: altLabel "asynchronous event-driven diffusion Monte Carlo" xsd:string {comment="EXACT"}
+property_value: definition "We present a novel Monte Carlo algorithm for N diffusing finite particles that react on collisions. Using the theory of first-passage processes and time dependent Green's functions, we break the difficult N-body problem into independent single- and two-body propagations circumventing numerous diffusion hops used in standard Monte Carlo simulations. The new algorithm is exact, extremely efficient, and applicable to many important physical situations in arbitrary integer dimensions." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1103/PhysRevLett.97.230602" xsd:anyURI {comment="T. Oppelstrup, V. V. Bulatov, G. H. Gilmer, M. H. Kalos, and B. Sadigh. First-passage Monte- Carlo algorithm: Diffusion without all the hops. Physical Review Letters, 97(23):230602, 2006."}
+
+[Term]
+id: KISAO_0000276
+name: Gill method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: altLabel "Gill's method" xsd:string {comment="EXACT"}
+property_value: altLabel "Runge-Kutta-Gill method" xsd:string {comment="EXACT"}
+property_value: definition "Gill's fourth order method is a Runge-Kutta method for approximating the solution of the initial value problem y'(x) = f(x,y);  y(x0) = y0 which evaluates the integrand,f(x,y), four times per step. This method is a fourth order procedure for which Richardson extrapolation can be used." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1017/S0305004100026414" xsd:anyURI {comment="Gill, S. 1951. A process for the step-by-step integration of differential equations in an automatic digital computing machine. Proc. Cambridge Philos. Soc., 47, pp 96-108."}
+
+[Term]
+id: KISAO_0000278
+name: Metropolis Monte Carlo algorithm
+is_a: KISAO_0000319 ! Monte Carlo method
+property_value: altLabel "Metropolis algorithm" xsd:string {comment="EXACT"}
+property_value: altLabel "Metropolis-Hastings algorithm" xsd:string {comment="EXACT"}
+property_value: definition "A general method, suitable for fast computing machines, for investigating such properties as equations of state for substances consisting of interacting individual molecules is described. The method consists of a modified Monte Carlo integration [http://identifiers.org/biomodels.kisao/KISAO_0000051] over configuration space." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "CompuCell3D" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.1699114" xsd:anyURI {comment="Metropolis, N.; Rosenbluth, A.W.; Rosenbluth, M.N.; Teller, A.H.; Teller, E. (1953). Equations of State Calculations by Fast Computing Machines. Journal of Chemical Physics 21 (6): 1087-1092."}
+
+[Term]
+id: KISAO_0000279
+name: Adams-Bashforth method
+is_a: KISAO_0000289 ! Adams method
+disjoint_from: KISAO_0000280 ! Adams-Moulton method
+property_value: altLabel "explicit Adams method" xsd:string {comment="EXACT"}
+property_value: definition "Given an initial value problem: y' = f(x,y),  y(x0) = y0 together with additional starting values y1 = y(x0 + h), . . . , yk-1 = y(x0 + (k-1) h) the k-step Adams-Bashforth method is an explicit linear multistep method that approximates the solution, y(x) at x = x0+kh, of the initial value problem by yk = yk - 1 + h * ( a0 f(xk - 1,yk - 1) + a1 f(xk - 2,yk - 2) + . . . + ak - 1 f(x0,y0) ), where a0, a1, . . . , ak - 1 are constants." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+
+[Term]
+id: KISAO_0000280
+name: Adams-Moulton method
+is_a: KISAO_0000289 ! Adams method
+property_value: altLabel "implicit Adams method" xsd:string {comment="EXACT"}
+property_value: definition "The (k-1)-step Adams-Moulton method is an implicit linear multistep method that iteratively approximates the solution, y(x) at x = x0+kh, of the initial value problem by yk = yk - 1 + h * ( b0 f(xk,yk) + b1 f(xk - 1,yk - 1) + . . . + bk - 1 f(x1,y1) ), where b1, . . . , bk - 1 are constants." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+
+[Term]
+id: KISAO_0000281
+name: multistep method
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: altLabel "multi-value method" xsd:string {comment="EXACT"}
+property_value: definition "A numerical method for differential equations which is based on several values of the solution." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+
+[Term]
+id: KISAO_0000282
+name: KINSOL
+is_a: KISAO_0000408 ! Newton-type method
+disjoint_from: KISAO_0000409 ! ordinary Newton method
+disjoint_from: KISAO_0000412 ! inexact Newton method
+relationship: KISAO_0000360 KISAO_0000354 ! Krylov subspace projection method
+property_value: altLabel "FKINSOL" xsd:string {comment="RELATED"}
+property_value: altLabel "Newton-Krylov solver for nonlinear algebraic systems" xsd:string {comment="RELATED"}
+property_value: altLabel "NKSOL" xsd:string {comment="RELATED"}
+property_value: definition "KINSOL solves algebraic systems in real N-space, written as F(u)=0,  F:RN->RN, given an initial guess u0. The basic method is either a modified or an inexact Newton iteration [http://identifiers.org/biomodels.kisao/KISAO_0000408]. The linear systems that arise are solved with either a direct (dense or banded) solver (serial version only), or one of the Krylov iterative solvers [http://identifiers.org/biomodels.kisao/KISAO_0000354]. In the Krylov case, the user can (optionally) supply a right preconditioner." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "SUNDIALS" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0911026" xsd:anyURI {comment="BROWN, P. N. AND SAAD, Y. 1990. Hybrid Krylov methods for nonlinear systems of equations. SIAM  J. Sci. Stat. Comput. 11, 450-481."}
+property_value: seeAlso "http://identifiers.org/doi/10.1145/1089014.1089020" xsd:anyURI {comment="Hindmarsh, A. C., et al., SUNDIALS: Suite of Nonlinear and Differential/Algebraic Equation Solvers, ACM Trans. Math. Softw., 31:363-396, 2005."}
+property_value: seeAlso "http://identifiers.org/doi/10.4249/scholarpedia.2860" xsd:anyURI {comment="Alan C. Hindmarsh and Radu Serban (2007) Sundails equation solvers, Scholarpedia, 2(3):2860."}
+
+[Term]
+id: KISAO_0000283
+name: IDA {comment="Alan C. Hindmarsh and Radu Serban (2007) Sundails equation solvers, Scholarpedia, 2(3):2860."}
+is_a: KISAO_0000432 ! IDA-like method
+relationship: KISAO_0000359 KISAO_0000355 ! DASPK
+relationship: KISAO_0000360 KISAO_0000288 ! backward differentiation formula
+relationship: KISAO_0000360 KISAO_0000354 ! Krylov subspace projection method
+relationship: KISAO_0000360 KISAO_0000386 ! scaled preconditioned generalized minimal residual method
+property_value: altLabel "implicit differential-algebraic solver" xsd:string {comment="EXACT"}
+property_value: altLabel "solver for differential-algebraic equation systems" xsd:string {comment="RELATED"}
+property_value: definition "IDA solves real differential-algebraic systems in N-space, in the general form F(t,y,y')=0,  y(t0)=y0,  y'(t0)=y'0. At each step, a Newton iteration [http://identifiers.org/biomodels.kisao/KISAO_0000408] leads to linear systems Jx=b, which are solved by one of five methods - two direct (dense or band; serial version only) and three Krylov [http://identifiers.org/biomodels.kisao/KISAO_0000354] (GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000353], BiCGStab [http://identifiers.org/biomodels.kisao/KISAO_0000392], or TFQMR [http://identifiers.org/biomodels.kisao/KISAO_0000396]).\nIDA is written in C, but derived from the package DASPK [http://identifiers.org/biomodels.kisao/KISAO_0000355] which is written in Fortran." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/opencor" xsd:anyURI {comment="OpenCOR"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: isImplementedIn "SUNDIALS" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0915088" xsd:anyURI {comment="BROWN, P. N., HINDMARSH, A. C., AND PETZOLD, L. R. 1994. Using Krylov methods in the solution of large-scale differential-algebraic systems. SIAM J. Sci. Comput. 15, 1467-1488."}
+property_value: seeAlso "http://identifiers.org/doi/10.1145/1089014.1089020" xsd:anyURI {comment="Hindmarsh, A. C., et al., SUNDIALS: Suite of Nonlinear and Differential/Algebraic Equation Solvers, ACM Trans. Math. Softw., 31:363-396, 2005."}
+property_value: seeAlso "http://identifiers.org/doi/10.4249/scholarpedia.2860" xsd:anyURI {comment="Alan C. Hindmarsh and Radu Serban (2007) Sundails equation solvers, Scholarpedia, 2(3):2860."}
+
+[Term]
+id: KISAO_0000285
+name: finite volume method
+is_a: KISAO_0000369 ! partial differential equation discretization method
+disjoint_from: KISAO_0000307 ! finite difference method
+property_value: altLabel "FVM" xsd:string {comment="EXACT"}
+property_value: definition "The finite volume method is a method for representing and evaluating partial differential equations in the form of algebraic equations, which attempts to emulate continuous conservation laws of physics." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: seeAlso "http://identifiers.org/isbn/0898715342" xsd:anyURI {comment="Y. Saad. 2003. Iterative Methods for Sparse Linear Systems (2nd ed.). Soc. for Industrial and Applied Math., Philadelphia, PA, USA."}
+
+[Term]
+id: KISAO_0000286
+name: Euler-Maruyama method
+is_a: KISAO_0000377 ! one-step method
+relationship: KISAO_0000361 KISAO_0000261 ! Euler method
+property_value: altLabel "stochastic Euler scheme" xsd:string {comment="EXACT"}
+property_value: definition "The Euler-Maruyama method is a method for the approximate numerical solution of a stochastic differential equation, which truncates the Ito and Stratonovich Taylor series of the exact solution after the first order stochastic terms. This converges to the Ito solution with strong global order accuracy 1/2 or weak global order accuracy 1. It is a simple generalization of the Euler method [http://identifiers.org/biomodels.kisao/KISAO_0000261] for ordinary differential equations to stochastic differential equations." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1098/rspa.2003.1247" xsd:anyURI {comment="Burrage, K., Burrage, P.M. and Tian, T. (2004) Numerical methods for strong solutions of stochastic differential equations: an overview. Proceedings of the Royal Society of London Series A: Mathematical, Physical and Engineering Sciences, 460 (2041). pp. 373-402."}
+
+[Term]
+id: KISAO_0000287
+name: Milstein method
+is_a: KISAO_0000281 ! multistep method
+disjoint_from: KISAO_0000288 ! backward differentiation formula
+property_value: definition "The Milstein method is a technique for the approximate numerical solution of a stochastic differential equation." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/079233213X" xsd:anyURI {comment="Milstein M. G. Numerical Integration of Stochastic Differential Equations (Mathematics and Its Applications) Springer, 2004."}
+
+[Term]
+id: KISAO_0000288
+name: backward differentiation formula
+is_a: KISAO_0000281 ! multistep method
+disjoint_from: KISAO_0000289 ! Adams method
+property_value: altLabel "BDF" xsd:string {comment="EXACT"}
+property_value: altLabel "Gear method" xsd:string {comment="EXACT"}
+property_value: altLabel "Gear's method" xsd:string {comment="EXACT"}
+property_value: definition "The backward differentiation formulas (BDF) are implicit multistep methods based on the numerical differentiation of a given function and are wildly used for integration of stiff differential equations." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "ByoDyn" xsd:string
+property_value: isImplementedIn "GSL" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: seeAlso "http://identifiers.org/isbn/0136266061" xsd:anyURI {comment="C. William Gear. 1971. Numerical Initial Value Problems in Ordinary Differential Equations. Prentice Hall PTR, Upper Saddle River, NJ, USA."}
+
+[Term]
+id: KISAO_0000289
+name: Adams method
+is_a: KISAO_0000281 ! multistep method
+property_value: definition "Adams' methods are multi-step methods used for the numerical integration of initial value problems in Ordinary Differential Equations (ODE's). Adams' algorithm consists of two parts: firstly, a starting procedure which provides y1, ... , yk-1 ( approximations to the exact solution at the points x0 + h, ... , x0 + (k - 1)h ) and, secondly, a multistep formula to obtain an approximation to the exact solution y(x0 + kh). This is then applied recursively, based on the numerical approximation of k successive steps, to compute y(x0 + (k + 1)h)." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "ByoDyn" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+
+[Term]
+id: KISAO_0000290
+name: Merson method
+is_a: KISAO_0000302 ! embedded Runge-Kutta method
+disjoint_from: KISAO_0000303 ! Zonneveld method
+property_value: altLabel "KM" xsd:string {comment="EXACT"}
+property_value: altLabel "Kutta-Merson method" xsd:string {comment="EXACT"}
+property_value: altLabel "Merson's method" xsd:string {comment="EXACT"}
+property_value: altLabel "Runge-Kutta-Merson method" xsd:string {comment="EXACT"}
+property_value: definition "A five-stage Runge-Kutta method with fourth-order accuracy." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: seeAlso "http://nla.gov.au/nla.cat-vn870866" xsd:anyURI {comment="R.H. Merson, An operational method for the study of integration processes, in: Proceedings of the Symposium on Data Processing, Weapons Research Establishment, Salisbury, Australia, 1957, pp. 110-1-110-25."}
+
+[Term]
+id: KISAO_0000296
+name: Hammer-Hollingsworth method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: definition "The numerical integration of ordinary differential equations by the use of Gaussian quadrature methods." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "urn:issn:0891-6837" xsd:anyURI {comment="P. C. Hammer & J. W. Hollingsworth, Trapezoidal methods of approximating solutions of differential equations, MTAC, v. 9, 1955, pp. 92-96. MR 17, 302."}
+
+[Term]
+id: KISAO_0000297
+name: Lobatto method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: altLabel "implicit Runge-Kutta method based on Lobatto quadrature" xsd:string {comment="EXACT"}
+property_value: definition "There are three families of Lobatto methods, called IIIA, IIIB and IIIC. These are named after Rehuel Lobatto. All are implicit Runge-Kutta methods, have order 2s − 2 and they all have c1 = 0 and cs = 1." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "urn:issn:1088-6842(e)" xsd:anyURI {comment="J. C. Butcher, Integration processes based on Radau quadrature formulas, Math. Comp., v. 18, 1964, pp. 233-244."}
+
+[Term]
+id: KISAO_0000299
+name: Butcher-Kuntzmann method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: altLabel "Gauss method" xsd:string {comment="EXACT"}
+property_value: definition "From a theoretical point of view, the Butcher-Kuntzmann Runge-Kutta methods belong to the best step-by-step methods for nonstiff problems. These methods integrate first-order initial-value problems by means of formulas based on Gauss-Legendre quadrature, and combine excellent stability features with the property of superconvergence at the step points." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1002/zamm.19660460519" xsd:anyURI {comment="F. Ceschin, J. Kuntzmann, Problèmes différentiels de conditions initiales. Paris 1963. Dunod."}
+property_value: seeAlso "urn:issn:1088-6842(e)" xsd:anyURI {comment="Butcher, J. C. (1964) Implicit Runge-Kutta processes. Math. Comput. 18, 50-64."}
+
+[Term]
+id: KISAO_0000301
+name: Heun method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: altLabel "Heun's method" xsd:string {comment="EXACT"}
+property_value: definition "The method is named after Karl L. W. M. Heun and is a numerical procedure for solving ordinary differential equations (ODEs) with a given initial value. It can be seen as extension of the Euler method [http://identifiers.org/biomodels.kisao/KISAO_0000261] into two-stage second-order Runge-Kutta method." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+
+[Term]
+id: KISAO_0000302
+name: embedded Runge-Kutta method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: altLabel "embedded RK" xsd:string {comment="EXACT"}
+property_value: definition "An embedded Runge-Kutta method is a method in which two Runge-Kutta estimates are obtained using the same auxiliary functions ki but with a different linear combination of these functions so that one estimate has an order one greater than the other." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+
+[Term]
+id: KISAO_0000303
+name: Zonneveld method
+is_a: KISAO_0000302 ! embedded Runge-Kutta method
+disjoint_from: KISAO_0000305 ! Verner method
+property_value: definition "An embedded Runge-Kutta method [http://identifiers.org/biomodels.kisao/KISAO_0000302] of order 4(3), proposed by J.A. Zonneveld in 1964." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://trove.nla.gov.au/work/21424455" xsd:anyURI {comment="Zonneveld, J. A (1970). Automatic numerical integration Mathematisch Centrum, Amsterdam"}
+
+[Term]
+id: KISAO_0000304
+name: Radau method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: altLabel "implicit Runge-Kutta method based on Radau quadrature" xsd:string {comment="EXACT"}
+property_value: definition "Implicit Runge-Kutta methods based on Radau quadrature." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: seeAlso "urn:issn:1088-6842(e)" xsd:anyURI {comment="J. C. Butcher, Integration processes based on Radau quadrature formulas, Math. Comput., 18(1964), 233-244."}
+
+[Term]
+id: KISAO_0000305
+name: Verner method
+is_a: KISAO_0000302 ! embedded Runge-Kutta method
+property_value: altLabel "Verner's method" xsd:string {comment="EXACT"}
+property_value: definition "The first high order (6(5)) embedded Runge-Kutta formulas that avoid the drawback of giving identically zero error estimates for quadrature problems y' = f(x) were constructed by Verner in 1978." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0728027" xsd:anyURI {comment="J.H. Verner, Some Runge-Kutta formula pairs, SIAM J. Numer. Anal 28 (1991) 496-511"}
+
+[Term]
+id: KISAO_0000306
+name: Lagrangian sliding fluid element algorithm
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: altLabel "blood-tissue exchange method" xsd:string {comment="EXACT"}
+property_value: altLabel "BTEX" xsd:string {comment="EXACT"}
+property_value: altLabel "LSFEA" xsd:string {comment="EXACT"}
+property_value: definition "Because the analytic solutions to the partial differential equations require convolution integration, solutions are obtained relatively efficiently by a fast numerical method. Our approach centers on the use of a sliding fluid element algorithm for capillary convection, with the time step set equal to the length step divided by the fluid velocity. Radial fluxes by permeation between plasma, interstitial fluid, and cells and axial diffusion exchanges within each time step are calculated analytically. The method enforces mass conservation unless there is regional consumption." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: seeAlso "http://identifiers.org/pubmed/1449234" xsd:anyURI {comment="Bassingthwaighte JB, Chan IS, and Wang CY. Computationally efficient algorithms for capillary convection-permeation-diffusion models for blood-tissue exchange. Ann Biomed Eng 20: 687-725, 1992."}
+
+[Term]
+id: KISAO_0000307
+name: finite difference method
+is_a: KISAO_0000369 ! partial differential equation discretization method
+property_value: altLabel "FDM" xsd:string {comment="EXACT"}
+property_value: definition "The finite difference method is based on local approximations of the partial derivatives in a Partial Differential Equation, which are derived by low order Taylor series expansions." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/0898715342" xsd:anyURI {comment="Y. Saad. 2003. Iterative Methods for Sparse Linear Systems (2nd ed.). Soc. for Industrial and Applied Math., Philadelphia, PA, USA."}
+
+[Term]
+id: KISAO_0000308
+name: MacCormack method
+is_a: KISAO_0000307 ! finite difference method
+disjoint_from: KISAO_0000309 ! Crank-Nicolson method
+property_value: definition "In computational fluid dynamics, the MacCormack method is a widely used discretization scheme for the numerical solution of hyperbolic partial differential equations. This second-order finite difference method [http://identifiers.org/biomodels.kisao/KISAO_0000307] is introduced by R. W. MacCormack in 1969." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: seeAlso "http://identifiers.org/doi/10.2514/2.6901" xsd:anyURI {comment="MacCormack, R. W., The Effect of viscosity in hypervelocity impact cratering, AIAA Paper, 69-354 (1969)."}
+
+[Term]
+id: KISAO_0000309
+name: Crank-Nicolson method
+is_a: KISAO_0000307 ! finite difference method
+property_value: definition "In numerical analysis, the Crank-Nicolson method is a finite difference method [http://identifiers.org/biomodels.kisao/KISAO_0000307] used for numerically solving the heat equation and similar partial differential equations. It is a second-order method in time, implicit in time, and is numerically stable. The method was developed by John Crank and Phyllis Nicolson in the mid 20th century." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1007/BF02127704" xsd:anyURI {comment="Crank, J.; Nicolson, P. (1947). A practical method for numerical evaluation of solutions of partial differential equations of the heat conduction type. Proc. Camb. Phil. Soc. 43 (1): 50-67."}
+
+[Term]
+id: KISAO_0000310
+name: method of lines {comment="EXACT"}
+is_a: KISAO_0000369 ! partial differential equation discretization method
+property_value: altLabel "MOL" xsd:string {comment="EXACT"}
+property_value: altLabel "NMOL" xsd:string {comment="EXACT"}
+property_value: altLabel "NUMOL" xsd:string {comment="EXACT"}
+property_value: definition "The method of lines is a general technique for solving partial differential equations (PDEs) by typically using finite difference relationships for the spatial derivatives and ordinary differential equations for the time derivative." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/0126241309" xsd:anyURI {comment="Schiesser, W. E. (1991). The Numerical Method of Lines. Academic Press."}
+
+[Term]
+id: KISAO_0000314
+name: S-System power-law canonical differential equations solver
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: altLabel "ESSYNS GMA" xsd:string {comment="EXACT"}
+property_value: definition "Ordinary differential equations can be recast into a nonlinear canonical form called an S-system. Evidence for the generality of this class comes from extensive empirical examples that have been recast and from the discovery that sets of differential equations and functions, recognized as among the most general, are special cases of S-systems. Identification of this nonlinear canonical form suggests a radically different approach to numerical solution of ordinary differential equations. By capitalizing on the regular structure of S-systems, efficient formulas for a variable-order, variable-step Taylor-series method are developed. " xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0727042" xsd:anyURI {comment="Irvine, D.H. and Savageau, M.A., Efficient solution of nonlinear ordinary differential equations expressed in S-System canonical form, Siam. J. Numer. Anal., 27:704-735, 1990."}
+
+[Term]
+id: KISAO_0000315
+name: lattice gas automata
+is_a: KISAO_0000068 ! deterministic cellular automata update algorithm
+disjoint_from: KISAO_0000334 ! multiparticle lattice gas automata
+property_value: altLabel "lattice gas cellular automata" xsd:string {comment="EXACT"}
+property_value: altLabel "LGA" xsd:string {comment="EXACT"}
+property_value: altLabel "LGCA" xsd:string {comment="EXACT"}
+property_value: definition "Lattice gas automata methods are a series of cellular automata methods used to simulate fluid flows. From the LGCA, it is possible to derive the macroscopic Navier-Stokes equations." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/3-540-66973-6" xsd:anyURI {comment="Dieter A. Wolf-Gladrow (2000). Lattice-Gas Cellular Automata and Lattice Boltzmann Models. Springer."}
+
+[Term]
+id: KISAO_0000316
+name: enhanced Greens function reaction dynamics
+is_a: KISAO_0000056 ! Smoluchowski equation based method
+relationship: KISAO_0000359 KISAO_0000058 ! Greens function reaction dynamics
+property_value: altLabel "eGFRD" xsd:string {comment="EXACT"}
+property_value: altLabel "enhanced Greens function reaction dynamics" xsd:string {comment="EXACT"}
+property_value: definition "GFRD [http://identifiers.org/biomodels.kisao/KISAO_0000058] decomposes the multi­body reaction diffusion problem to a set of single and two body problems. Analytical solutions for two body reaction diffusion are available via Smoluchowski equation. eGFRD allows to solve each sub­problem asynchronously by introducing the concept of first passage processes." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1007/978-3-540-88562-7_3" xsd:anyURI {comment="K. Takahashi, An exact Brownian dynamics method for cell simulation, in Computational Methods in Systems Biology, vol. 5307/2008."}
+
+[Term]
+id: KISAO_0000317
+name: E-Cell multi-algorithm simulation method
+is_a: KISAO_0000352 ! hybrid method
+property_value: definition "A modular meta-algorithm with a discrete event scheduler that can incorporate any type of time-driven simulation algorithm. It was shown that this meta-algorithm can efficiently drive simulation models with different simulation algorithms with little intrusive modification to the algorithms themselves. Only a few additional methods to handle communications between computational modules are required." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell"}
+property_value: seeAlso "http://identifiers.org/pubmed/14990450" xsd:anyURI {comment="Takahashi, K., Kaizu, K., Hu, B., and Tomita, M., A multi-algorithm, multi-timescale method for cell simulation. Bioinformatics, in press."}
+
+[Term]
+id: KISAO_0000318
+name: Gauss-Legendre Runge-Kutta method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: altLabel "Open Formula" xsd:string {comment="EXACT"}
+property_value: definition "So called 'Open Formula', two points formula, three points formula, four points formula, five points formula and six points formula of the Runge-Kutta method to solve the initial value problem of the ordinary differential equation. These formulas use the points and weights from the Gauss-Legendre Quadrature formulas for finding the value of the definite integral." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: seeAlso "http://identifiers.org/isbn/960-8457-54-8" xsd:anyURI {comment="Maitree Podisuk, Sirirat Khuntidilokwongsa, and Witchaya Rattanametawee. 2006. Gauss-Legendre Quadrature formula in Runge-Kutta method with modified model of Newton cooling law. In Proceedings of the 8th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering (MMACTEE'06). World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wisconsin, USA, 312-317."}
+
+[Term]
+id: KISAO_0000319
+name: Monte Carlo method
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: altLabel "MC" xsd:string {comment="EXACT"}
+property_value: definition "Monte Carlo methods (or Monte Carlo experiments) are a class of computational algorithms that rely on repeated random sampling to compute their results." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://identifiers.org/doi/10.2307/2280232" xsd:anyURI {comment="Metropolis, N.; Ulam, S. (1949). \"The Monte Carlo Method\". Journal of the American Statistical Association (American Statistical Association) 44 (247): 335-341."}
+
+[Term]
+id: KISAO_0000320
+name: BioRica hybrid method
+is_a: KISAO_0000352 ! hybrid method
+property_value: definition "The simulation schema for a given BioRica node is given by a hybrid algorithm that deals with continuous time and allows for discrete events that roll back the time according to these discrete interruptions." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "BioRica" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/19425152" xsd:anyURI {comment="Cvijovic M, Soueidan H, Sherman DJ, Klipp E, Nikolski M. Exploratory simulation of cell ageing using hierarchical models. Genome Inform. 2008;21:114-25."}
+
+[Term]
+id: KISAO_0000321
+name: Cash-Karp method
+is_a: KISAO_0000435 ! embedded Runge-Kutta 5(4) method
+property_value: definition "An family of explicit Runge-Kutta formulas, which are very efficient for problems with smooth solution as well as problems having rapidly varying solutions. Each member of this family consists of a fifty-order formula that contains embedded formulas of all orders 1 through 4. By computing solutions at several different orders, it is possible to detect sharp fronts or discontinuities before all the function evaluations defining the full Runge-Kutta step have been computed." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "Cain" xsd:string
+property_value: isImplementedIn "GSL" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1145/79505.79507" xsd:anyURI {comment="J. R. Cash, A. H. Karp. \"A variable order Runge-Kutta method for initial value problems with rapidly varying right-hand sides\", ACM Transactions on Mathematical Software 16: 201-222, 1990."}
+
+[Term]
+id: KISAO_0000323
+name: equation-free probabilistic steady-state approximation
+is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
+property_value: definition "We present a probabilistic steady-state approximation that separates the time scales of an arbitrary reaction network, detects the convergence of a marginal distribution to a quasi-steady-state, directly samples the underlying distribution, and uses those samples to accurately predict the state of the system, including the effects of the slow dynamics, at future times. The numerical method produces an accurate solution of both the fast and slow reaction dynamics while, for stiff systems, reducing the computational time by orders of magnitude. The developed theory makes no approximations on the shape or form of the underlying steady-state distribution and only assumes that it is ergodic. <...> The developed theory may be applied to any type of kinetic Monte Carlo simulation to more efficiently simulate dynamically stiff systems, including existing exact, approximate, or hybrid stochastic simulation techniques.\n" xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2131050" xsd:anyURI {comment="Salis H, Kaznessis YN. An equation-free probabilistic steady-state approximation: dynamic application to the stochastic simulation of biochemical reaction networks. J Chem Phys. 2005 Dec 1;123(21):214106."}
+
+[Term]
+id: KISAO_0000324
+name: nested stochastic simulation algorithm
+is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
+relationship: KISAO_0000360 KISAO_0000029 ! Gillespie direct algorithm
+property_value: altLabel "nested SSA" xsd:string {comment="EXACT"}
+property_value: definition "This multiscale method is a small modification of the Gillespie's direct method [http://identifiers.org/biomodels.kisao/KISAO_0000029], in the form of a nested SSA, with inner loops for the fast reactions, and outer loop for the slow reactions. The number of groups can be more than two, and the grouping into fast and slow  variables can be done dynamically in an adaptive version of the scheme." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/16321076" xsd:anyURI {comment="E W., Liu D. and Vanden-Eijnden E. Nested stochastic simulation algorithm for chemical kinetic systems with disparate rates. J Chem Phys. 2005 Nov 15;123(19):194107.\n"}
+
+[Term]
+id: KISAO_0000329
+name: constant-time kinetic Monte Carlo algorithm
+is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
+property_value: altLabel "SSA-CR" xsd:string {comment="EXACT"}
+property_value: definition "The computational cost of the original SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] scaled linearly with the number of reactions in the network. Gibson and Bruck developed a logarithmic scaling version of the SSA which uses a priority queue or binary tree for more efficient reaction selection [http://identifiers.org/biomodels.kisao/KISAO_0000027]. More generally, this problem is one of dynamic discrete random variate generation which finds many uses in kinetic Monte Carlo and discrete event simulation. We present here a constant-time algorithm, whose cost is independent of the number of reactions, enabled by a slightly more complex underlying data structure." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/18513044" xsd:anyURI {comment="Slepoy A, Thompson AP, Plimpton SJ. A constant-time kinetic Monte Carlo algorithm for simulation of large biochemical reaction networks. J Chem Phys. 2008 May 28;128(20):205101."}
+
+[Term]
+id: KISAO_0000330
+name: R-leaping algorithm
+is_a: KISAO_0000621 ! stochastic simulation leaping method
+property_value: altLabel "R-leap method" xsd:string {comment="EXACT"}
+property_value: definition "A novel algorithm is proposed for the acceleration of the exact stochastic simulation algorithm by a predefined number of reaction firings (R-leaping) that may occur across several reaction channels. In the present approach, the numbers of reaction firings are correlated binomial distributions and the sampling procedure is independent of any permutation of the reaction channels. This enables the algorithm to efficiently handle large systems with disparate rates, providing substantial computational savings in certain cases." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/16964997" xsd:anyURI {comment="Auger A, Chatelain P, Koumoutsakos P. R-leaping: accelerating the stochastic simulation algorithm by reaction leaps. J Chem Phys. 2006 Aug 28;125(8):084103."}
+
+[Term]
+id: KISAO_0000331
+name: exact R-leaping algorithm
+is_a: KISAO_0000621 ! stochastic simulation leaping method
+relationship: KISAO_0000359 KISAO_0000330 ! R-leaping algorithm
+property_value: altLabel "ER-leap method" xsd:string {comment="EXACT"}
+property_value: altLabel "exact accelerated stochastic simulation algorithm" xsd:string {comment="EXACT"}
+property_value: altLabel "exact R-leap method" xsd:string {comment="EXACT"}
+property_value: definition "We present a SSA which, similar to R-leap [http://identifiers.org/biomodels.kisao/KISAO_0000330], accelerates SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] by executing multiple reactions per algorithmic step, but which samples the reactant trajectories from the same probability distribution as the SSA. This 'exact R-leap' or 'ER-leap' algorithm is a modification of the R-leap algorithm which is both exact and capable of substantial speed-up over SSA." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/2852436" xsd:anyURI {comment="Eric Mjolsness, David Orendorff, Philippe Chatelain, and Petros Koumoutsakos. An exact accelerated stochastic simulation algorithm. J Chem Phys. 2009 April 14; 130(14): 144110."}
+
+[Term]
+id: KISAO_0000333
+name: accelerated stochastic simulation algorithm
+is_a: KISAO_0000241 ! Gillespie-like method
+relationship: KISAO_0000359 KISAO_0000029 ! Gillespie direct algorithm
+property_value: altLabel "accelerated SSA" xsd:string {comment="EXACT"}
+property_value: definition "An algorithm, which accelerates SSA [http://identifiers.org/biomodels.kisao/KISAO_0000029] either at the expense of its accuracy or exact." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000334
+name: multiparticle lattice gas automata
+is_a: KISAO_0000068 ! deterministic cellular automata update algorithm
+relationship: KISAO_0000359 KISAO_0000315 ! lattice gas automata
+property_value: altLabel "multiparticle lattice gas cellular automata" xsd:string {comment="EXACT"}
+property_value: definition "An algorithm which allows  for an arbitrary number of particles, while keeping the benefits of the cellular automata approach [http://identifiers.org/biomodels.kisao/KISAO_0000315]." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1142/S0129183194000052" xsd:anyURI {comment="Chopard B., et al.Multiparticle lattice gas automata for reaction diffusion systems. Int. J. Mod. Phys. C 1994;5:47-63."}
+
+[Term]
+id: KISAO_0000335
+name: generalized stochastic simulation algorithm
+is_a: KISAO_0000241 ! Gillespie-like method
+relationship: KISAO_0000361 KISAO_0000029 ! Gillespie direct algorithm
+property_value: definition "Gillespie direct method [http://identifiers.org/biomodels.kisao/KISAO_0000029] follows unit-by-unit changes in the total numbers of each reactant species, it is especially well suited to the study of systems in which reactant densities are low and the application of methods based on continuum approximations, such as the traditional ordinary differential equations of chemical kinetics, is questionable. The 'generalized stochastic simulation algorithm' branch presents methods, which extend Gillespie direct method [http://identifiers.org/biomodels.kisao/KISAO_0000029] to suit to systems with other characteristics." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000336
+name: D-leaping method
+is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
+property_value: definition "We propose a novel, accelerated algorithm for the approximate stochastic simulation of biochemical systems with delays. The present work extends existing accelerated algorithms by distributing, in a time adaptive fashion, the delayed reactions so as to minimize the computational effort while preserving their accuracy." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1016/j.jcp.2009.05.004" xsd:anyURI {comment="Bayati B, Chatelain P, Koumoutsakos. D-leaping: Accelerating stochastic simulation algorithms for reactions with delays. Journal of Computational Physics. 2009 Sept;228(16):5909-5918."}
+
+[Term]
+id: KISAO_0000337
+name: finite element method
+is_a: KISAO_0000369 ! partial differential equation discretization method
+property_value: altLabel "FEA" xsd:string {comment="EXACT"}
+property_value: altLabel "FEM" xsd:string {comment="EXACT"}
+property_value: altLabel "finite element analysis" xsd:string {comment="EXACT"}
+property_value: definition "A numerical technique for finding approximate solutions of partial differential equations (PDE) as well as of integral equations. The solution approach is based either on eliminating the differential equation completely (steady state problems), or rendering the PDE into an approximating system of ordinary differential equations, which are then numerically integrated using standard techniques such as Euler method [http://identifiers.org/biomodels.kisao/KISAO_0000261], Runge-Kutta [http://identifiers.org/biomodels.kisao/KISAO_0000064], etc." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1109/MAP.2007.376627" xsd:anyURI {comment="Pelosi G. The finite-element method, Part I: R. L. Courant: Historical Corner. IEEE Antennas and Propagation Magazine, Vol. 49, No. 2. (April 2007), pp. 180-182."}
+
+[Term]
+id: KISAO_0000338
+name: h-version of the finite element method
+is_a: KISAO_0000337 ! finite element method
+disjoint_from: KISAO_0000339 ! p-version of the finite element method
+property_value: altLabel "h-FEM" xsd:string {comment="EXACT"}
+property_value: altLabel "h-method" xsd:string {comment="EXACT"}
+property_value: definition "Classical form of the 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337], in which polynomials of fixed degree p are used and the mesh is refined to increase accuracy. Can be considered as a special case of the h-p version [http://identifiers.org/biomodels.kisao/KISAO_0000340]." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1016/0168-874X(94)90003-5" xsd:anyURI {comment="Babuska, I., T. Strouboulis, A. Mathur, C. S. Upadhyay, Pollution error in the h-version of the finite element method and the local quality of a-posteriori error estimators, Finite Elements in Analysis and Design, 17: 273-321, 1994."}
+
+[Term]
+id: KISAO_0000339
+name: p-version of the finite element method
+is_a: KISAO_0000337 ! finite element method
+property_value: altLabel "p-FEM" xsd:string {comment="EXACT"}
+property_value: altLabel "p-method" xsd:string {comment="EXACT"}
+property_value: definition "The p version of 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] uses a fixed mesh but increases the polynomial degree p to increase accuracy. Can be considered as a special case of the h-p version [http://identifiers.org/biomodels.kisao/KISAO_0000340]." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0718033" xsd:anyURI {comment="Babuska, I., B.A. Szabo and I.N. Katz, The p-version of the finite element method, SIAM J. Numer. Anal., 18: 515-545, 1981."}
+
+[Term]
+id: KISAO_0000340
+name: h-p version of the finite element method
+is_a: KISAO_0000337 ! finite element method
+disjoint_from: KISAO_0000341 ! mixed finite element method
+relationship: KISAO_0000361 KISAO_0000338 ! h-version of the finite element method
+relationship: KISAO_0000361 KISAO_0000339 ! p-version of the finite element method
+property_value: altLabel "hp-FEM" xsd:string {comment="EXACT"}
+property_value: altLabel "hp-method" xsd:string {comment="EXACT"}
+property_value: definition "In h-p version of 'finite difference method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] the two approaches of mesh refinement and degree enchacement are combined." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1007/BF00272624" xsd:anyURI {comment="Babuska, I., and B. Guo, The h-p version of the finite element method, Comput. Mech., 1: 203-220, 1986."}
+
+[Term]
+id: KISAO_0000341
+name: mixed finite element method
+is_a: KISAO_0000337 ! finite element method
+property_value: definition "A 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] in which both stress and displacement fields are approximated as primary variables." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1016/0045-7825(90)90168-L" xsd:anyURI {comment="D. N. Arnold. 1990. Mixed finite element methods for elliptic problems. Comput. Methods Appl. Mech. Eng. 82, 1-3 (September 1990), 281-300."}
+
+[Term]
+id: KISAO_0000342
+name: level set method
+is_a: KISAO_0000369 ! partial differential equation discretization method
+property_value: altLabel "level-set method" xsd:string {comment="EXACT"}
+property_value: altLabel "LSM" xsd:string {comment="EXACT"}
+property_value: definition "An algorithm for moving surfaces under their curvature. This algorithm rely on numerically solving Hamilton-Jacobi equations with viscous terms, using approximation techniques from hyperbolic conservation laws." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1016/0021-9991(88)90002-2" xsd:anyURI {comment="Osher, S.; Sethian, J. A. (1988), \"Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations\", J. Comput. Phys. 79: 12-49."}
+
+[Term]
+id: KISAO_0000343
+name: generalized finite element method
+is_a: KISAO_0000369 ! partial differential equation discretization method
+relationship: KISAO_0000361 KISAO_0000337 ! finite element method
+property_value: altLabel "GFEM" xsd:string {comment="EXACT"}
+property_value: altLabel "partition of unity method" xsd:string {comment="EXACT"}
+property_value: altLabel "PUM" xsd:string {comment="EXACT"}
+property_value: definition "The GFEM is a generalization of the classical 'finite element method' [http://identifiers.org/biomodels.kisao/KISAO_0000337] — in its h [http://identifiers.org/biomodels.kisao/KISAO_0000338], p [http://identifiers.org/biomodels.kisao/KISAO_0000339], and h-p versions [http://identifiers.org/biomodels.kisao/KISAO_0000340]— as well as of the various forms of meshless methods used in engineering." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1142/S0219876204000083" xsd:anyURI {comment="Babuska, Ivo; Uday Banerjee, John E. Osborn (June 2004). Generalized Finite Element Methods: Main Ideas, Results, and Perspective. International Journal of Computational Methods 1 (1): 67-103."}
+
+[Term]
+id: KISAO_0000345
+name: h-p cloud method
+is_a: KISAO_0000369 ! partial differential equation discretization method
+property_value: altLabel "h-p clouds" xsd:string {comment="EXACT"}
+property_value: altLabel "method of clouds" xsd:string {comment="EXACT"}
+property_value: definition "A meshless method, which uses a partition of unity to construct the family of h-p cloud functions. " xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1002/(SICI)1098-2426(199611)12:6<673::AID-NUM3>3.0.CO;2-P" xsd:anyURI {comment="Duarte, C. A. and Oden, J. T. (1996), H-p clouds—an h-p meshless method. Numerical Methods for Partial Differential Equations, 12: 673-705."}
+
+[Term]
+id: KISAO_0000348
+name: extended finite element method
+is_a: KISAO_0000369 ! partial differential equation discretization method
+relationship: KISAO_0000361 KISAO_0000337 ! finite element method
+property_value: altLabel "X-FEM" xsd:string {comment="EXACT"}
+property_value: altLabel "XFEM" xsd:string {comment="EXACT"}
+property_value: definition "A numerical method to model arbitrary discontinuities in continuous bodies that does not require the mesh to conform to the discontinuities nor significant mesh refinement near singularities. In X-FEM the standard finite element approximation [http://identifiers.org/biomodels.kisao/KISAO_0000337] is enriched and the approximation space is extended by an additional family of functions." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1007/s00466-002-0391-2" xsd:anyURI {comment="Stazi, F. L.; Budyn, E.; Chessa, J.; Belytschko, T. An extended finite element method with higher-order elements for curved cracks. Computational Mechanics, Volume 31, Issue 1-2, pp. 38-48 (2003)."}
+
+[Term]
+id: KISAO_0000349
+name: method of finite spheres
+is_a: KISAO_0000369 ! partial differential equation discretization method
+property_value: altLabel "MFS" xsd:string {comment="EXACT"}
+property_value: definition "Method of finite spheres is truly meshless in the sense that the nodes are placed and the numerical integration is performed without a mesh. Some of the novel features of the method of finite spheres are the numerical integration scheme and the way in which the Dirichlet boundary conditions are incorporated." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1007/s004660050481" xsd:anyURI {comment="S. De and K. J. Bathe. The method of finite spheres. Computational Mechanics, Volume 25, Number 4, 329-345."}
+
+[Term]
+id: KISAO_0000350
+name: probability-weighted dynamic Monte Carlo method
+is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
+property_value: altLabel "probability-weighted DMC" xsd:string {comment="EXACT"}
+property_value: altLabel "PW-DMC" xsd:string {comment="EXACT"}
+property_value: definition "We have developed a probability-weighted DMC method by incorporating the weighted sampling algorithm of equilibrium molecular simulations. This new algorithm samples the slow reactions very efficiently and makes it possible to simulate in a computationally efficient manner the reaction kinetics of physical systems in which the rates of reactions vary by several orders of magnitude." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1021/jp011404w" xsd:anyURI {comment="Resat H, Wiley HS, Dixon DA. Probability-weighted dynamic Monte Carlo method for reaction kinetics simulations. J Phys Chem B. 2001;105:11026-11034."}
+
+[Term]
+id: KISAO_0000351
+name: multinomial tau-leaping method
+is_a: KISAO_0000039 ! tau-leaping method
+relationship: KISAO_0000361 KISAO_0000074 ! binomial tau-leaping method
+property_value: altLabel "MtauL" xsd:string {comment="EXACT"}
+property_value: definition "The multinomial tau-leaping method  is an extension of the binomial tau-leaping method [http://identifiers.org/biomodels.kisao/KISAO_0000074] to networks with arbitrary multiple-channel reactant dependencies. Improvements were achieved by a combination of three factors: First, tau-leaping steps are determined simply and efficiently using a-priori information and Poisson distribution based estimates of expectation values for reaction numbers. Second, networks are partitioned into closed groups of reactions and corresponding reactants in which no group reactant set is found in any other group. Third, product formation is factored into upper bound estimation of the number of times a particular reaction occurs." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/17343434" xsd:anyURI {comment="Pettigrew MF, Resat H. Multinomial tau-leaping method for stochastic kinetic simulations. J Chem Phys. 2007 Feb 28;126(8):084101."}
+
+[Term]
+id: KISAO_0000352
+name: hybrid method
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+relationship: KISAO_0000246 KISAO_0000000 ! modelling and simulation algorithm
+property_value: definition "A simulation methods which combines the advantages of complementary simulation approaches: the whole system is subdivided into appropriate parts and different simulation methods operate on these parts at the same time." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000353
+name: generalized minimal residual algorithm
+is_a: KISAO_0000354 ! Krylov subspace projection method
+disjoint_from: KISAO_0000357 ! conjugate gradient method
+relationship: KISAO_0000361 KISAO_0000388 ! minimal residual method
+property_value: altLabel "GMRES" xsd:string {comment="EXACT"}
+property_value: definition "An iterative method for solving linear systems, which has the property of minimizing at every step the norm of the residual vector over a Krylov subspace. The generalized minimal residual method extends the minimal residual method (MINRES) [http://identifiers.org/biomodels.kisao/KISAO_0000388], which is only applicable to symmetric systems, to non-symmetric systems." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "CVODE" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0907058" xsd:anyURI {comment="Youcef Saad and Martin H. Schultz, GMRES: A Generalized Minimal Residual Algorithm for Solving Nonsymmetric Linear Systems. SIAM J. Sci. and Stat. Comput. 7, 856 (1986)."}
+
+[Term]
+id: KISAO_0000354
+name: Krylov subspace projection method
+is_a: KISAO_0000398 ! iterative method for solving a system of linear equations
+property_value: altLabel "Krylov subspace method" xsd:string {comment="EXACT"}
+property_value: definition "Krylov subspace method is an iterative linear equation method, which builds up Krylov subspaces and look for good approximations to eigenvectors and invariant subspaces within the Krylov spaces." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/0898715342" xsd:anyURI {comment="Y. Saad. 2003. Iterative Methods for Sparse Linear Systems (2nd ed.). Soc. for Industrial and Applied Math., Philadelphia, PA, USA."}
+
+[Term]
+id: KISAO_0000355
+name: DASPK
+is_a: KISAO_0000432 ! IDA-like method
+relationship: KISAO_0000359 KISAO_0000283 ! IDA
+relationship: KISAO_0000360 KISAO_0000353 ! generalized minimal residual algorithm
+relationship: KISAO_0000360 KISAO_0000356 ! DASSL
+relationship: KISAO_0000360 KISAO_0000386 ! scaled preconditioned generalized minimal residual method
+property_value: altLabel "DDASPK" xsd:string {comment="NARROW"}
+property_value: altLabel "differential algebraic system solver with Krylov preconditioning" xsd:string {comment="EXACT"}
+property_value: altLabel "SDASPK" xsd:string {comment="NARROW"}
+property_value: definition "In DASPK, we have combined the time-stepping methods of DASSL [http://identifiers.org/biomodels.kisao/KISAO_0000255] with preconditioned iterative method GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000386], for solving large-scale systems of DAEs of the form F(t, y, y') = 0, where F, y, y' are N-dimensional vectors, and a consistent set of initial conditions y(t0) = y0, y'(t0) = y'0 is given.\nDASPK is written in Fortran." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0915088" xsd:anyURI {comment="Peter N. Brown, Alan C. Hindmarsh, and Linda R. Petzold. 1994. Using Krylov methods in the solution of large-scale differential-algebraic systems. SIAM J. Sci. Comput. 15, 6 (November 1994), 1467-1488."}
+
+[Term]
+id: KISAO_0000356
+name: DASSL
+is_a: KISAO_0000432 ! IDA-like method
+property_value: altLabel "DDASSL" xsd:string {comment="NARROW"}
+property_value: altLabel "differential algebraic system solver" xsd:string {comment="EXACT"}
+property_value: altLabel "SDASSL" xsd:string {comment="NARROW"}
+property_value: definition "DASSL is designed for the numerical solution of implicit systems of differential/algebraic equations written in the form F(t,y,y')=0, where F, y, and y' are vectors, and initial values for y and y' are given." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://www.nea.fr/abs/html/nesc9918.html" xsd:anyURI {comment="Linda R. Petzold: A Description of DASSL: A Differential/Algebraic System Solver, SAND82-8637 (September 1982)."}
+
+[Term]
+id: KISAO_0000357
+name: conjugate gradient method
+is_a: KISAO_0000354 ! Krylov subspace projection method
+property_value: altLabel "CG" xsd:string {comment="EXACT"}
+property_value: definition "Conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is symmetric and positive-definite. The conjugate gradient method is an iterative method, so it can be applied to sparse systems that are too large to be handled by direct methods. Such systems often arise when numerically solving partial differential equations." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "urn:issn:0091-0635" xsd:anyURI {comment="M. R. Hestenes and E. L. Stiefel, Methods of conjugate gradients for solving linear systems. J. Res. Natl. Bur. Stand. 49 (1952), p. 409."}
+
+[Term]
+id: KISAO_0000358
+name: biconjugate gradient method
+is_a: KISAO_0000354 ! Krylov subspace projection method
+relationship: KISAO_0000361 KISAO_0000357 ! conjugate gradient method
+property_value: altLabel "BCG" xsd:string {comment="EXACT"}
+property_value: altLabel "Bi-CG" xsd:string {comment="EXACT"}
+property_value: altLabel "BiCG" xsd:string {comment="EXACT"}
+property_value: definition "The biconjugate gradient method provides a generalization of conjugate gradient method [http://identifiers.org/biomodels.kisao/KISAO_0000357] to non-symmetric matrices." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1007/BFb0080109" xsd:anyURI {comment="Fletcher, R. (1976). \"Conjugate gradient methods for indefinite systems\". Numerical Analysis. Lecture Notes in Mathematics (Springer Berlin / Heidelberg) 506: 73-89."}
+
+[Term]
+id: KISAO_0000362
+name: implicit-state Doob-Gillespie algorithm
+is_a: KISAO_0000017 ! multi-state agent-based simulation method
+relationship: KISAO_0000359 KISAO_0000021 ! StochSim nearest-neighbour algorithm
+relationship: KISAO_0000361 KISAO_0000029 ! Gillespie direct algorithm
+property_value: definition "The algorithm uses a representation of the system together with a super-approximation of its ‘event horizon’ (all events that may happen next), and a specific correction scheme to obtain exact timings. Being completely local and not based on any kind of enumeration, this algorithm has a per event time cost which is independent of (i) the size of the set of generable species (which can even be infinite), and (ii) independent of the size of the system (ie, the number of agent instances). The algorithm can be refined, using concepts derived from the classical notion of causality, so that in addition to the above one also has that the even cost is depending (iii) only logarithmically on the size of the model (ie, the number of rules).\n" xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/3-540-76636-7 978-3-540-76636-0" xsd:anyURI {comment="V. Danos, J. Feret, W. Fontana, and J. Krivine. 2007. Scalable simulation of cellular signalling networks. In Proceedings of the 5th Asian conference on Programming languages and systems (APLAS'07), Zhong Shao (Ed.). Springer-Verlag, Berlin, Heidelberg, 139-157."}
+
+[Term]
+id: KISAO_0000363
+name: rule-based simulation method
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: definition "Rule-based models provide a powerful alternative to approaches that require explicit enumeration of all possible molecular species of a system. Such models consist of formal rules governing interactive behaviour. Rule-based simulation methods simulate such models." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000364
+name: Adams predictor-corrector method
+is_a: KISAO_0000289 ! Adams method
+relationship: KISAO_0000360 KISAO_0000279 ! Adams-Bashforth method
+relationship: KISAO_0000360 KISAO_0000280 ! Adams-Moulton method
+property_value: definition "The combination of evaluating a single explicit integration method ('Adams-Bashforth method' [http://identifiers.org/biomodels.kisao/KISAO_0000279]) (the predictor step) in order to provide a good initial guess for the successive evaluation of an implicit method ('Adams-Moulton method' [http://identifiers.org/biomodels.kisao/KISAO_0000280]) (the corrector step) using iteration." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "GSL" xsd:string
+property_value: seeAlso "urn:asin:B0000EFQ8B" xsd:anyURI {comment="Moulton, Forest R. (1926), New methods in exterior ballistics, University of Chicago Press."}
+
+[Term]
+id: KISAO_0000365
+name: NDSolve method
+is_a: KISAO_0000352 ! hybrid method
+relationship: KISAO_0000246 KISAO_0000288 ! backward differentiation formula
+relationship: KISAO_0000246 KISAO_0000302 ! embedded Runge-Kutta method
+relationship: KISAO_0000246 KISAO_0000310 ! method of lines
+relationship: KISAO_0000246 KISAO_0000364 ! Adams predictor-corrector method
+relationship: KISAO_0000246 KISAO_0000367 ! partitioned Runge-Kutta method
+property_value: definition "The Mathematica computation system function NDSolve is a general numerical differential equation solver. It can handle a wide range of ordinary differential equations as well as some partial differential equations. NDSolve can also solve some differential-algebraic equations, which are typically a mix of differential and algebraic equations." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "Mathematica" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-1-57955-058-5" xsd:anyURI {comment="Advanced Numerical Differential Equation Solving in Mathematica, Wolfram Mathematica Tutorial Collection, 2008."}
+
+[Term]
+id: KISAO_0000367
+name: partitioned Runge-Kutta method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+relationship: KISAO_0000360 KISAO_0000064 {minCardinality="2"} ! Runge-Kutta based method
+property_value: altLabel "PRK" xsd:string {comment="EXACT"}
+property_value: altLabel "SPRK" xsd:string {comment="EXACT"}
+property_value: altLabel "symplectic partitioned Runge-Kutta method" xsd:string {comment="EXACT"}
+property_value: definition "If a Hamiltonian system possesses a natural partitioning, it is possible to integrate its certain components using one Runge-Kutta method and other components using a different Runge-Kutta method. The overall s-stage scheme is called a partitioned Runge-Kutta method." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1007/BF01389456" xsd:anyURI {comment="P. Rentrop (1985): Partitioned Runge-Kutta methods with stiffness detection and stepsize control. Numer. Math., Vol. 47, p.545-564."}
+
+[Term]
+id: KISAO_0000369
+name: partial differential equation discretization method
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: definition "A method which solves partial differential equations by discretizing them, i.e. approximating them by equations that involve a finite number of unknowns." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000377
+name: one-step method
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: definition "A numerical method for differential equations which uses one starting value at each step." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+
+[Term]
+id: KISAO_0000378
+name: implicit midpoint rule
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: altLabel "implicit Gaussian second order Runge-Kutta method" xsd:string {comment="EXACT"}
+property_value: definition "The implicit midpoint rule is a second-order case of the more general implicit s-stage Runge-Kutta methods [http://identifiers.org/biomodels.kisao/KISAO_0000064 and (http://identifiers.org/biomodels.kisao/KISAO_0000245 some http://identifiers.org/biomodels.kisao/KISAO_0000240)]." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "GSL" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag."}
+
+[Term]
+id: KISAO_0000379
+name: Bulirsch-Stoer algorithm
+is_a: KISAO_0000380 ! Richardson extrapolation based method
+relationship: KISAO_0000360 KISAO_0000382 ! modified midpoint method
+property_value: altLabel "GBS" xsd:string {comment="EXACT"}
+property_value: altLabel "Gragg-Bulirsch-Stoer algorithm" xsd:string {comment="EXACT"}
+property_value: definition "The Bulirsch-Stoer method is an adaptive method which uses Gragg's modified midpoint method [http://identifiers.org/biomodels.kisao/KISAO_0000382] to estimate the solution of an initial value problem for various step sizes. The estimates are fit to a \"diagonal\" rational function or a polynomial as a function of the step size and the limit as the step size tends to zero is taken as the final estimate." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1007/BF02165234" xsd:anyURI {comment="Bulirsch R. and Stoer J. (1966) Numerical treatment of ordinary differential equations by extrapolation methods, Numerische Mathematik, Volume 8, Number 1, 1-13."}
+
+[Term]
+id: KISAO_0000380
+name: Richardson extrapolation based method
+is_a: KISAO_0000377 ! one-step method
+property_value: definition "A method based on ideas of Richardson extrapolation, which is a process for obtaining increased accuracy in a discretized approximation by extrapolating results from coarse discretizations to an arbitrarily fine one." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://identifiers.org/doi/10.1098/rsta.1911.0009" xsd:anyURI {comment="Richardson, L. F. (1911). The approximate arithmetical solution by finite differences of physical problems including differential equations, with an application to the stresses in a masonry dam. Philosophical Transactions of the Royal Society of London, Series A 210 (459-470): 307-357."}
+
+[Term]
+id: KISAO_0000381
+name: midpoint method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: definition "The midpoint method is an explicit method for approximating the solution of the initial value problem y' = f(x,y);  y(x0) = y0 at x for a given step size h. For the midpoint method the derivative of y(x) is approximated by the symmetric difference y'(x) = ( y(x+h) - y(x-h) ) / 2h + O(h2)." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag."}
+
+[Term]
+id: KISAO_0000382
+name: modified midpoint method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: altLabel "Gragg's method" xsd:string {comment="EXACT"}
+property_value: altLabel "Gragg's modified midpoint method" xsd:string
+property_value: definition "The modified midpoint method is globally a second order method for approximating the solution of the initial value problem y' = f(x, y), y(x0) = y0, which advances a vector of dependent variables y(x) from a point x to a point x + H by a sequence of n substeps each of size h, h = H/n.\n" xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/052143064X" xsd:anyURI {comment="Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical Recipes in Fortran 77. Cambridge University Press (2001)."}
+
+[Term]
+id: KISAO_0000383
+name: Bader-Deuflhard method
+is_a: KISAO_0000380 ! Richardson extrapolation based method
+relationship: KISAO_0000360 KISAO_0000384 ! semi-implicit midpoint rule
+relationship: KISAO_0000361 KISAO_0000379 ! Bulirsch-Stoer algorithm
+property_value: definition "The Bader-Deuflhard method is an extrapolation method based on a semi-implicit discretization [http://identifiers.org/biomodels.kisao/KISAO_0000387]. It is a generalization of the Bulirsch-Stoer algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000379] for solving ordinary differential equations." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "GSL" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1007/BF01418331" xsd:anyURI {comment="Bader, G. and Deuflhard, P. \"A Semi-Implicit Mid-Point Rule for Stiff Systems of Ordinary Differential Equations.\" Numer. Math. 41, 373-398, 1983."}
+
+[Term]
+id: KISAO_0000384
+name: semi-implicit midpoint rule
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: definition "A semi-implicit version of the midpoint method that has an even error series [http://identifiers.org/biomodels.kisao/KISAO_0000381]." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1007/BF01418331" xsd:anyURI {comment="Bader, G. and Deuflhard, P. \"A Semi-Implicit Mid-Point Rule for Stiff Systems of Ordinary Differential Equations.\" Numer. Math. 41, 373-398, 1983."}
+
+[Term]
+id: KISAO_0000386
+name: scaled preconditioned generalized minimal residual method
+is_a: KISAO_0000353 ! generalized minimal residual algorithm
+relationship: KISAO_0000360 KISAO_0000397 ! preconditioning technique
+property_value: altLabel "SPGMR" xsd:string {comment="EXACT"}
+property_value: definition "A scaled preconditioned version of 'generalized minimal residual algorithm' [http://identifiers.org/biomodels.kisao/KISAO_0000353]. For linear system Ax = b a preconditioner matrix P that approximates A is sought, for which linear system Px = b can be solved easily. Preconditioning is applied on the left only. Scaling is done using diagonal matrix D whose diagonal elements are weights w^i = rtol|y^i| +atol^i, where rtol is 'relative tolerance' [http://identifiers.org/biomodels.kisao/KISAO_0000209] and atol is 'absolute tolerance' [http://identifiers.org/biomodels.kisao/KISAO_0000211]." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0915088" xsd:anyURI {comment="Peter N. Brown, Alan C. Hindmarsh, and Linda R. Petzold. 1994. Using Krylov methods in the solution of large-scale differential-algebraic systems. SIAM J. Sci. Comput. 15, 6 (November 1994), 1467-1488."}
+
+[Term]
+id: KISAO_0000388
+name: minimal residual method
+is_a: KISAO_0000354 ! Krylov subspace projection method
+property_value: altLabel "MINRES" xsd:string {comment="EXACT"}
+property_value: definition "The 'minimal residual method' is an algorithm for the numerical solution of indefinite symmertic systems of linear equations." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0712047" xsd:anyURI {comment="Paige C.C., Saunders M.A. Solution of sparse indefinite systems of linear equations, SIAM Journal on Numerical Analysis (1975) Volume: 12, Issue: 4, Publisher: SIAM, Pages: 617-629."}
+
+[Term]
+id: KISAO_0000389
+name: quasi-minimal residual method
+is_a: KISAO_0000393 ! ingenious conjugate gradients-squared method
+property_value: altLabel "QMR" xsd:string {comment="EXACT"}
+property_value: definition "The QMR algorithm is a robust iterative solver for general nonsingular non-Hermitian linear systems. The method uses a robust implementation of the look-ahead Lanczos algorithm to generate basis vectors for the Krylov subspaces Kn(r0, A). The QMR iterates are characterized by a quasi-minimal residual property over Kn(r0, A)." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1007/BF01385726" xsd:anyURI {comment="Roland W. Freund and Noël M. Nachtigal. QMR: a quasi-minimal residual method for non-Hermitian linear systems. NUMERISCHE MATHEMATIK Volume 60, Number 1, 315-339.\n"}
+
+[Term]
+id: KISAO_0000392
+name: biconjugate gradient stabilized method
+is_a: KISAO_0000395 ! improved biconjugate gradient method
+disjoint_from: KISAO_0000393 ! ingenious conjugate gradients-squared method
+property_value: altLabel "Bi-CGSTAB" xsd:string {comment="EXACT"}
+property_value: altLabel "BiCGSTAB" xsd:string {comment="EXACT"}
+property_value: definition "An iterative method for the numerical solution of nonsymmetric linear systems. It is a variant of the biconjugate gradient method (BiCG) [http://identifiers.org/biomodels.kisao/KISAO_0000358] and has faster and smoother convergence than the original BiCG." xsd:string
+property_value: isImplementedIn "CVODE" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0913035" xsd:anyURI {comment="Van der Vorst, H. A. (1992). Bi-CGSTAB: A Fast and Smoothly Converging Variant of Bi-CG for the Solution of Nonsymmetric Linear Systems. SIAM Journal on Scientific and Statistical Computing 13: 631-644."}
+
+[Term]
+id: KISAO_0000393
+name: ingenious conjugate gradients-squared method
+is_a: KISAO_0000395 ! improved biconjugate gradient method
+property_value: altLabel "CGS" xsd:string {comment="EXACT"}
+property_value: definition "A Lanczos-type method for nonsymmetric sparse linear systems. The method is based on a polynomial variant of the conjugate gradients algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000357]. Although related to the so-called bi-conjugate gradients (Bi-CG) algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000358], it does not involve adjoint matrix-vector multiplications, and the expected convergence rate is about twice that of the Bi-CG algorithm." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0910004" xsd:anyURI {comment="Peter Sonneveld. 1989. CGS, a fast Lanczos-type solver for nonsymmetric linear systems. SIAM J. Sci. Stat. Comput. 10, 1 (January 1989), 36-52."}
+
+[Term]
+id: KISAO_0000394
+name: quasi-minimal residual variant of biconjugate gradient stabilized method
+is_a: KISAO_0000392 ! biconjugate gradient stabilized method
+property_value: altLabel "QMRCGSTAB" xsd:string {comment="EXACT"}
+property_value: definition "QMRCGSTAB is a quasi-minimal residual (QMR) variant of the Bi-CGSTAB algorithm [http://identifiers.org/biomodels.kisao/KISAO_0000394] of van der Vorst for solving nonsymmetric linear systems. The motivation for the QMR variant is to obtain smoother convergence behavior of the underlying method.\n" xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0915023" xsd:anyURI {comment="T. F. Chan, E. Gallopoulos, V. Simoncini, T. Szeto, and C. H. Tong. 1994. A quasi-minimal residual variant of the Bi-CGSTAB algorithm for nonsymmetric systems. SIAM J. Sci. Comput. 15, 2 (March 1994), 338-347."}
+
+[Term]
+id: KISAO_0000395
+name: improved biconjugate gradient method
+is_a: KISAO_0000354 ! Krylov subspace projection method
+relationship: KISAO_0000359 KISAO_0000358 ! biconjugate gradient method
+property_value: definition "An 'improved biconjugate gradient method' branch contains algorithms which can be viewed as improvements over some of drawbacks of BCG [http://identifiers.org/biomodels.kisao/KISAO_0000358], such as (1) the need for matrix-vector multiplications with A^T (which can be inconvenient as well as doubling the number of matrix-vector multiplications compared to CG [http://identifiers.org/biomodels.kisao/KISAO_0000357] for each increase in the degree of the underlying Krylov subspace), (2) the possibility of breakdowns and (3) erratic convergence behavior.\n" xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000396
+name: transpose-free quasi-minimal residual algorithm
+is_a: KISAO_0000389 ! quasi-minimal residual method
+property_value: altLabel "TFQMR" xsd:string {comment="EXACT"}
+property_value: definition "A version of CGS [http://identifiers.org/biomodels.kisao/KISAO_0000393] which 'quasi-minimizes' the residual in the space spanned by the vectors generated by the CGS iteration.\n" xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "CVODE" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0914029" xsd:anyURI {comment="Roland W. Freund. 1993. A transpose-free quasi-minimal residual algorithm for non-Hermitian linear systems. SIAM J. Sci. Comput. 14, 2 (March 1993), 470-482."}
+
+[Term]
+id: KISAO_0000397
+name: preconditioning technique
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+relationship: KISAO_0000399 KISAO_0000398 ! iterative method for solving a system of linear equations
+property_value: definition "Preconditioning is simply a means of transforming the original linear system into one which has the same solution, but which is likely to be easier to solve with an iterative solver." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/0898715342" xsd:anyURI {comment="Saad, Yousef (2003). Iterative methods for sparse linear systems (2nd ed.). SIAM."}
+
+[Term]
+id: KISAO_0000398
+name: iterative method for solving a system of linear equations
+is_a: KISAO_0000624 ! method for solving a system of linear equations
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://identifiers.org/isbn/0898715342" xsd:anyURI {comment="Saad, Yousef (2003). Iterative methods for sparse linear systems (2nd ed.). SIAM."}
+
+[Term]
+id: KISAO_0000407
+name: steady state method
+comment: Requested by Frank T. Bergmann on Sunday, November 27, 2011 4:45:30 PM.
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+is_a: KISAO_0000622 ! flux balance method
+property_value: definition "A method looking for a steady state of a dynamic system." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000408
+name: Newton-type method
+comment: Requested by Frank T. Bergmann on Sunday, November 27, 2011 4:45:30 PM.
+is_a: KISAO_0000631 ! iterative root-finding method
+property_value: definition "A method which attacks the solution of a nonlinear problem F(x) = 0 by solving a sequence of liner problems of the same kind.\nThe solution of the system F(x)=0 can be interpreted as a steady state of a dynamic system x'(t)=F(x(t)). The Newton approach will only work if the fixed point [http://identifiers.org/biomodels.teddy/TEDDY_0000086] of the dinamic system is attractive [http://identifiers.org/biomodels.teddy/TEDDY_0000094]." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/9783540210993" xsd:anyURI {comment="Deuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms, Springer Series in Computational Mathematics, Vol. 35, 1st ed. 2004."}
+
+[Term]
+id: KISAO_0000409
+name: ordinary Newton method
+is_a: KISAO_0000408 ! Newton-type method
+property_value: definition "A 'Newton-type method' [http://identifiers.org/biomodels.kisao/KISAO_0000408] which solves the general nonlinear problem F(x)=0 by applying successive linearization F'(x[k])deltax[k]=-F(x[k]), x[k+1]=x[k]+deltax[k], k=0,1,..." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/9783540210993" xsd:anyURI {comment="Deuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms, Springer Series in Computational Mathematics, Vol. 35, 1st ed. 2004."}
+
+[Term]
+id: KISAO_0000410
+name: simlified Newton method
+is_a: KISAO_0000408 ! Newton-type method
+property_value: definition "A 'Newton-type method' [http://identifiers.org/biomodels.kisao/KISAO_0000408] which is characterized by keeping the initial derivative throughout the whole iteration: F'(x[0])deltax[k]=-F(x[k]), x[k+1]=x[k]+deltax[k], k=0,1,..." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/9783540210993" xsd:anyURI {comment="Deuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms, Springer Series in Computational Mathematics, Vol. 35, 1st ed. 2004."}
+
+[Term]
+id: KISAO_0000411
+name: Newton-like method
+is_a: KISAO_0000408 ! Newton-type method
+property_value: definition "A 'Newton-type method' [http://identifiers.org/biomodels.kisao/KISAO_0000408] which is characterized by the fact that, in finite dimension, the Jacodian matrices are either replaced by some fixed 'close by' Jacobian F'(z) with z not equal to the initial guess x[0], or by some approximation so that: M'(x[0])deltax[k]=-F(x[k]), x[k+1]=x[k]+deltax[k], k=0,1,..." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/9783540210993" xsd:anyURI {comment="Deuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms, Springer Series in Computational Mathematics, Vol. 35, 1st ed. 2004."}
+
+[Term]
+id: KISAO_0000412
+name: inexact Newton method
+is_a: KISAO_0000408 ! Newton-type method
+property_value: altLabel "iterative Newton method" xsd:string {comment="EXACT"}
+property_value: altLabel "truncated Newton method" xsd:string {comment="EXACT"}
+property_value: definition "For extremely large scale nonlinear problems the arising linear systems for the Newton corrections can no longer be solved directly ('exactly'), but must be solved iterativly ('inexactly) - which gives the name inexact Newton methods. The whole scheme then consists of an inner iteration (at Newton step k): \nF'(x[k])deltaxi[k]=-F(x[k])+ri[k], k=0,1,...\nxi[k+1]=x[k]+deltaxi[k], i=0,1,..,imax[k]\nin terms of residuals ri[k] and an outer iteration where, given x[0], the iterates are defined as x[k+1]=xi[k+1] for i=imax[k], k=0,1,..." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/9783540210993" xsd:anyURI {comment="Deuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms, Springer Series in Computational Mathematics, Vol. 35, 1st ed. 2004."}
+
+[Term]
+id: KISAO_0000413
+name: exact Newton method
+is_a: KISAO_0000408 ! Newton-type method
+property_value: altLabel "direct Newton method" xsd:string
+property_value: definition "Any of the finite dimensional Newton-type methods [http://identifiers.org/biomodels.kisao/KISAO_0000408] requires the numerical solution of the linear equations F'(x[k])deltax[k]=-F(x[k]). Whenever direct elimination methods are applicable, we speak of exact Newton methods." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/9783540210993" xsd:anyURI {comment="Deuflhard, P. Newton Methods for Nonlinear Problems: Affine Invariance and Adaptive Algorithms, Springer Series in Computational Mathematics, Vol. 35, 1st ed. 2004."}
+
+[Term]
+id: KISAO_0000416
+name: partial least squares regression method
+comment: Requested by Kristin Tøndel on Thursday, October 13, 2011 10:46:04 AM.
+is_a: KISAO_0000423 ! partial least squares regression-like method
+disjoint_from: KISAO_0000417 ! hierarchical cluster-based partial least squares regression method
+property_value: altLabel "PLSR" xsd:string {comment="EXACT"}
+property_value: altLabel "PLSR method" xsd:string {comment="EXACT"}
+property_value: definition "Multivariate regression method based on estimated latent variables. Related to Principal Component Analysis (PCA) and Principal Component Regression (PCR)." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/biomodels.kisao/10.1007/BFb0062108" xsd:anyURI {comment="Wold S, Martens H, Wold H (1983) The multivariate calibration method in chemistry solved by the PLS method. In: Lecture notes in Mathematics, Matrix Pencils. Heidelberg: Springer-Verlag. pp. 286-293."}
+
+[Term]
+id: KISAO_0000417
+name: hierarchical cluster-based partial least squares regression method
+comment: Requested by Kristin Tøndel on Thursday, October 13, 2011 11:13:17 AM.
+is_a: KISAO_0000423 ! partial least squares regression-like method
+relationship: KISAO_0000360 KISAO_0000416 ! partial least squares regression method
+property_value: altLabel "HC-PLSR" xsd:string
+property_value: altLabel "Multivariate regression method based on separating the observations into clusters and generating Partial Least Squares Regression (PLSR) [http://identifiers.org/biomodels.kisao/KISAO_0000416] models within each cluster. This local regression analysis is suitable for very non-linear systems. PLSR is a regression method based on estimated latent variables, related to Principal Component Analysis (PCA) and Principal Component Regression (PCR).\nHierarchical cluster-based partial least squares regression method uses fuzzy C-means clustering, PLSR and Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA) or Naive Bayes for classification of new observations to be predicted." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1186/1752-0509-5-90" xsd:anyURI {comment="Tøndel K, Indahl UG, Gjuvsland AB, Vik JO, Hunter P, et al. (2011) Hierarchical Cluster-based Partial Least Squares Regression is an efficient tool for metamodelling of nonlinear dynamic models. BMC Systems Biology 5: 90."}
+
+[Term]
+id: KISAO_0000418
+name: N-way partial least squares regression method
+comment: Requested by Kristin Tøndel on Thursday, October 13, 2011 11:33:06 AM.
+is_a: KISAO_0000423 ! partial least squares regression-like method
+property_value: altLabel "N-PLS" xsd:string {comment="EXACT"}
+property_value: altLabel "N-way partial least squares method" xsd:string {comment="EXACT"}
+property_value: altLabel "N-way PLSR" xsd:string {comment="EXACT"}
+property_value: definition "Multivariate regression method that can be used on N-way data. Based on Partial Least Squares Regression (PLSR) [http://identifiers.org/biomodels.kisao/KISAO_0000416], which is a regression method based on estimated latent variables. PLSR is related to Principal Component Analysis (PCA) and Principal Component Regression (PCR)." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1002/(SICI)1099-128X(199601)10:1<47::AID-CEM400>3.0.CO;2-C" xsd:anyURI {comment="Bro R (1996) Multiway calibration. Multilinear PLS. J. Chemometrics 10: 47-6."}
+property_value: seeAlso "http://www.models.life.ku.dk/nwaytoolbox" xsd:anyURI {comment="N-way toolbox website"}
+
+[Term]
+id: KISAO_0000419
+name: metamodelling method
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: definition "Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://identifiers.org/doi/10.1186/1752-0509-5-90" xsd:anyURI {comment="Tøndel K, Indahl UG, Gjuvsland AB, Vik JO, Hunter P, et al. (2011) Hierarchical Cluster-based Partial Least Squares Regression is an efficient tool for metamodelling of nonlinear dynamic models. BMC Systems Biology 5: 90."}
+
+[Term]
+id: KISAO_0000423
+name: partial least squares regression-like method
+is_a: KISAO_0000419 ! metamodelling method
+property_value: definition "Method for building regression models between independent and dependent variables." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000432
+name: IDA-like method
+is_a: KISAO_0000408 ! Newton-type method
+property_value: definition "Solves real differential-algebraic systems in N-space, in the general form F(t,y,y')=0,  y(t0)=y0,  y'(t0)=y'0. At each step, a Newton iteration [http://identifiers.org/biomodels.kisao/KISAO_0000408] leads to linear systems Jx=b, which are solved by one of five methods - two direct (dense or band; serial version only) and three Krylov [http://identifiers.org/biomodels.kisao/KISAO_0000354] (GMRES [http://identifiers.org/biomodels.kisao/KISAO_0000353], BiCGStab [http://identifiers.org/biomodels.kisao/KISAO_0000392], or TFQMR [http://identifiers.org/biomodels.kisao/KISAO_0000396])." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://identifiers.org/doi/10.1145/1089014.1089020" xsd:anyURI {comment="Hindmarsh, A. C., et al., SUNDIALS: Suite of Nonlinear and Differential/Algebraic Equation Solvers, ACM Trans. Math. Softw., 31:363-396, 2005."}
+
+[Term]
+id: KISAO_0000433
+name: CVODE-like method
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: definition "Solves ODE initial value problems, in real N-space, written as y'=f(t,y),  y(t0)=y0. It is capable for stiff and non-stiff systems and uses two different linear multi-step methods, namely the Adam-Moulton [http://identifiers.org/biomodels.kisao/KISAO_0000280] method and the backward differentiation formula [http://identifiers.org/biomodels.kisao/KISAO_0000288]." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://identifiers.org/doi/10.1145/1089014.1089020" xsd:anyURI {comment="Hindmarsh, A. C., et al., SUNDIALS: Suite of Nonlinear and Differential/Algebraic Equation Solvers, ACM Trans. Math. Softw., 31:363-396, 2005."}
+
+[Term]
+id: KISAO_0000434
+name: Higham-Hall method
+is_a: KISAO_0000435 ! embedded Runge-Kutta 5(4) method
+property_value: altLabel "RK5(4)7FEql" xsd:string
+property_value: definition "The equilibrium theory of Hall and Higham (1988) can be used to determine whether a Runge-Kutta algorithm will perform smoothly when stability restricts the stepsize. Higham-Hall method is a fifth order embedded Runge-Kutta method [http://identifiers.org/biomodels.kisao/KISAO_0000302], which behaves smoothly with respect to the standard type of stepsize controllers." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1016/0377-0427(90)90192-3" xsd:anyURI {comment="Higham, D.J. and Hall, G. (1990) Embedded Runge-Kutta formulae with stable equilibrium states. Journal of Computational and Applied Mathematics, 29 (1). pp. 25-33."}
+
+[Term]
+id: KISAO_0000435
+name: embedded Runge-Kutta 5(4) method
+is_a: KISAO_0000302 ! embedded Runge-Kutta method
+property_value: altLabel "RK5(4)" xsd:string
+property_value: definition "An embedded Runge-Kutta integrator of order 5(4)." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000436
+name: Dormand-Prince 8(5,3) method
+is_a: KISAO_0000302 ! embedded Runge-Kutta method
+property_value: definition "This method is based on an 8(6) method by Dormand and Prince (i.e. order 8 for the integration and order 6 for error estimation) modified by Hairer and Wanner to use a 5th order error estimator with 3rd order correction." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/978-3-540-56670-0" xsd:anyURI {comment="Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems (2nd ed.), Berlin: Springer Verlag"}
+
+[Term]
+id: KISAO_0000437
+name: flux balance analysis
+comment: Requested by Frank T. Bergmann on Thursday, November 29, 2012 9:51:58 AM.
+is_a: KISAO_0000407 ! steady state method
+is_a: KISAO_0000622 ! flux balance method
+disjoint_from: KISAO_0000526 ! flux variability analysis
+property_value: altLabel "FBA" xsd:string
+property_value: definition "Flux balance analysis is a mathematical approach for analyzing the flow of metabolites through a metabolic network." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1038/nbt.1614" xsd:anyURI {comment="Jeffrey D Orth, Ines Thiele and Bernhard O Palsson (2010) What is flux balance analysis? Nature Biotechnology 28, 245–248"}
+
+[Term]
+id: KISAO_0000447
+name: COAST
+comment: Requested by Mark Moeller on Friday, January 25, 2013 11:11:30 AM.
+is_a: KISAO_0000352 ! hybrid method
+property_value: altLabel "controllable approximative stochastic reaction algorithm" xsd:string
+property_value: definition "An approximative algorithm for stochastic simulations of chemical reaction systems based on three different modeling levels: for small numbers of particles an exact [http://identifiers.org/biomodels.kisao/KISAO_0000236] stochastic [http://identifiers.org/biomodels.kisao/KISAO_0000104] model; for intermediate numbers an approximative [http://identifiers.org/biomodels.kisao/KISAO_0000237], but computationally more efficient stochastic [http://identifiers.org/biomodels.kisao/KISAO_0000104] model based on discrete Gaussian distributions; and for large numbers the deterministic [http://identifiers.org/biomodels.kisao/KISAO_0000103] reaction kinetics. In every simulation time step, the subdivision of the reaction channels into the three different modeling levels is done automatically, where all approximations applied can be controlled by a single error parameter for which an appropriate value can easily be found." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/17100426" xsd:anyURI {comment="Holger Wagner, Mark Moeller, and Klaus Prank (2006) COAST: Controllable approximative stochastic reaction algorithm. J. Chem. Phys. 125, 174104"}
+
+[Term]
+id: KISAO_0000448
+name: logical model simulation method
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: definition "Qualitative (logical) models specify the evolution rules of their components. In each state a number of transitions are enabled. A 'logical model simulation method' guides the choice of the transitions processed at each step." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://www.identifiers.org/pubmed/22141422" xsd:anyURI {comment="Daniel Machado et al. Modeling formalisms in Systems Biology. AMB Express 2011, 1:45"}
+
+[Term]
+id: KISAO_0000449
+name: synchronous logical model simulation method
+is_a: KISAO_0000448 ! logical model simulation method
+disjoint_from: KISAO_0000450 ! asynchronous logical model simulation method
+property_value: definition "Qualitative (logical) models specify the evolution rules of their components. In the case of a synchronous updating all enabled transitions are processed simultaneously. " xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+
+[Term]
+id: KISAO_0000450
+name: asynchronous logical model simulation method
+is_a: KISAO_0000448 ! logical model simulation method
+property_value: definition "Qualitative (logical) models specify the evolution rules of their components. It the case of an asynchronous updating all enabled transitions are performed independently: a state has as many successors as the number of transitions enabled in this state. An 'asynchronous logical model simulation method' specifies a rule to guide the choice of a unique transition at each step (for example random)." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+
+[Term]
+id: KISAO_0000468
+name: maximal timestep method
+comment: Requested by Andrzej Kierzek on Thursday, April 24, 2014 12:40:35 PM
+comment: Used to simulate systems involving reactions with propensities varying by many orders of magnitude.
+is_a: KISAO_0000352 ! hybrid method
+relationship: KISAO_0000360 KISAO_0000027 ! Gibson-Bruck next reaction algorithm
+relationship: KISAO_0000360 KISAO_0000039 ! tau-leaping method
+property_value: definition "Hybrid simulation algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000352] combining Gibson and Bruck algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000027] with the Gillespie tau-leap method [http://www.biomodels.net/kisao/KISAO#KISAO_0000039]." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/pubmed/14990466" xsd:anyURI {comment="Puchalka J, Kierzek AM. Bridging the gap between stochastic and deterministic regimes in the kinetic simulations of the biochemical reaction networks. Biophys J. 2004 Mar;86(3):1357-72.\n"}
+
+[Term]
+id: KISAO_0000470
+name: optimization algorithm
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: altLabel "optimization method" xsd:string
+property_value: definition "An optimization algorithm tries to find the minumum or maximum of an arbitrary function. It takes a function of one or several variables and determines the values for the variables so that the function value is optimal." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://en.wikipedia.org/wiki/Mathematical_optimization#Optimization_algorithms" xsd:anyURI
+property_value: seeAlso "http://identifiers.org/isbn/0691102872" xsd:anyURI {comment="Brinkhuis J, Tikhomirov V. Optimization: Insights and Applications\nPrinceton Series in Applied Mathematics (illustrated), Princeton University Press, 2005."}
+
+[Term]
+id: KISAO_0000471
+name: local optimization algorithm
+is_a: KISAO_0000470 ! optimization algorithm
+disjoint_from: KISAO_0000472 ! global optimization algorithm
+property_value: altLabel "local optimiation method" xsd:string
+property_value: definition "A local optimization algorithm is an optimisation algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000470] that only finds a local optimum of a function. If several optima exist for the function, it usually depends on the starting values for the variables which optimum is found." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+
+[Term]
+id: KISAO_0000472
+name: global optimization algorithm
+is_a: KISAO_0000470 ! optimization algorithm
+property_value: altLabel "global optimization method" xsd:string
+property_value: definition "A global optimization algorithm is an optimization algorithm [http://www.biomodels.net/kisao/KISAO#KISAO_0000470] that tries to find the global optimum of a function. If a function has several minima/maxima with in the allowed range of variable values, the global minimum/maximum is the one with the smallest/largest function value." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+
+[Term]
+id: KISAO_0000473
+name: Bayesian inference algorithm
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: definition "A bayesian inference algorithm calculates a posterior probability distribution from a prior probability distribution and some additional evidence in the form of a likelyhood function." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://en.wikipedia.org/wiki/Bayesian_inference" xsd:anyURI
+property_value: seeAlso "http://identifiers.org/isbn/111803144X" xsd:anyURI {comment="George E. P. Box, George C. Tiao. Bayesian Inference in Statistical Analysis, Volume 40 of Wiley Classics Library. John Wiley & Sons (reprint, revised), 2011."}
+
+[Term]
+id: KISAO_0000491
+name: discrete event simulation algorithm
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: altLabel "DES" xsd:string
+property_value: definition "Discrete Event Simulation algorithm refers to the simulation of systems whose (countable) discrete states change over time and are event-driven." xsd:string
+property_value: seeAlso "http://identifiers.org/isbn/0387333320" xsd:anyURI {comment="C.G. Cassandras & S. Lafortune \"Introduction to Discrete Event Systems\", Chapt 1 2nd Ed 2008. Springer"}
+
+[Term]
+id: KISAO_0000496
+name: CVODES
+comment: CVODES is a superset of CVODE [http://identifiers.org/biomodels.kisao/KISAO_0000019] and hence all options available to CVODE (with the exception of the FCVODE interface module) are also available for CVODES. Both integration methods (Adams-Moulton [http://identifiers.org/biomodels.kisao/KISAO_0000280] and BDF [http://identifiers.org/biomodels.kisao/KISAO_0000288]) and the corresponding nonlinear iteration methods, as well as all linear solver and preconditioner modules, are available for the integration of the original ODEs, the sensitivity systems, or the adjoint system.
+is_a: KISAO_0000433 ! CVODE-like method
+relationship: KISAO_0000359 KISAO_0000019 ! CVODE
+relationship: KISAO_0000360 KISAO_0000497 ! KLU
+property_value: definition "CVODES is a solver for stiff and nonstiff ODE systems (initial value problem) given in explicit form y’ = f(t,y,p) with sensitivity analysis capabilities (both forward and adjoint modes)." xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/amici" xsd:anyURI {comment="AMICI"}
+property_value: isImplementedIn "SUNDIALS" xsd:string
+property_value: seeAlso "http://computation.llnl.gov/projects/sundials/cvodes" xsd:anyURI
+
+[Term]
+id: KISAO_0000497
+name: KLU
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: altLabel "\"Clark Kent\" LU factorization algorithm" xsd:string
+property_value: definition "KLU is a software package and an algorithm for solving sparse unsymmetric linear systems of equations that arise in circuit simulation applications. It relies on a permutation to Block Triangular Form (BTF), several methods for finding a fill-reducing ordering (variants of approximate minimum degree and nested dissection), and Gilbert/Peierls’ sparse left-looking LU factorization algorithm to factorize each block. The package is written in C and includes a MATLAB interface." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1145/1824801.1824814" xsd:anyURI {comment="Davis, Timothy A., and Ekanathan Palamadai Natarajan. \"Algorithm 907: KLU, a direct sparse solver for circuit simulation problems.\" ACM Transactions on Mathematical Software (TOMS) 37.3 (2010): 36."}
+
+[Term]
+id: KISAO_0000499
+name: dynamic flux balance analysis
+comment: Ticket 32
+is_a: KISAO_0000352 ! hybrid method
+is_a: KISAO_0000622 ! flux balance method
+relationship: KISAO_0000246 KISAO_0000437 ! flux balance analysis
+property_value: altLabel "DFBA" xsd:string
+property_value: definition "Dynamic flux balance analysis (DFBA) enables the simulation of dynamic biological systems by assuming organisms reach steady state rapidly in response to changes in the extracellular environment. DFBA couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+property_value: seeAlso "http://identifiers.org/doi/10.1186/s12859-014-0409-8" xsd:anyURI {comment="DFBAlab: a fast and reliable MATLAB code for dynamic flux balance analysis.\nGomez JA, Höffner K, Barton PI. BMC Bioinformatics. 2014 Dec 18;15:409."}
+
+[Term]
+id: KISAO_0000500
+name: SOA-DFBA
+comment: Ticket 32
+is_a: KISAO_0000499 ! dynamic flux balance analysis
+disjoint_from: KISAO_0000501 ! DOA-DFBA
+relationship: KISAO_0000360 KISAO_0000030 ! Euler forward method
+property_value: altLabel "SOA" xsd:string
+property_value: altLabel "static optimization approach dynamic flux balance analysis" xsd:string
+property_value: definition "Dynamic Flux Balance Analysis (DFBA) [http://identifiers.org/biomodels.kisao/KISAO_0000499] couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches. The static optimization approach (SOA) uses the Euler forward method [http://identifiers.org/biomodels.kisao/KISAO_0000030], solving the embedded LPs at each time step. The FBA fluxes are assumed to be constant during the time step." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "DFBAlab" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1186/s12859-014-0409-8" xsd:anyURI {comment="DFBAlab: a fast and reliable MATLAB code for dynamic flux balance analysis.\nGomez JA, Höffner K, Barton PI. BMC Bioinformatics. 2014 Dec 18;15:409."}
+
+[Term]
+id: KISAO_0000501
+name: DOA-DFBA
+comment: Ticket 32
+is_a: KISAO_0000499 ! dynamic flux balance analysis
+property_value: altLabel "DOA" xsd:string
+property_value: altLabel "dynamic optimization approach dynamic flux balance analysis" xsd:string
+property_value: definition "Dynamic Flux Balance Analysis (DFBA) [http://identifiers.org/biomodels.kisao/KISAO_0000499] couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches. The dynamic optimization approach (DOA) discretizes the time horizon and optimizes simultaneously over the entire time period of interest by solving a nonlinear programming problem (NLP)." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "DFBAlab" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1186/s12859-014-0409-8" xsd:anyURI {comment="DFBAlab: a fast and reliable MATLAB code for dynamic flux balance analysis.\nGomez JA, Höffner K, Barton PI. BMC Bioinformatics. 2014 Dec 18;15:409."}
+
+[Term]
+id: KISAO_0000502
+name: DA-DFBA
+comment: Ticket 32
+is_a: KISAO_0000499 ! dynamic flux balance analysis
+property_value: altLabel "DA" xsd:string
+property_value: altLabel "direct approach dynamics flux balance analysis" xsd:string
+property_value: definition "Dynamic Flux Balance Analysis (DFBA) [http://identifiers.org/biomodels.kisao/KISAO_0000499] couples flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model approaches with dynamic model approaches. The direct approach (DA) includes the LP solver in the right-hand side evaluator for the ordinary differential equations (ODEs) and takes advantage of reliable implicit ODE integrators with adaptive step size for error control." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "DFBAlab" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1186/s12859-014-0409-8" xsd:anyURI {comment="DFBAlab: a fast and reliable MATLAB code for dynamic flux balance analysis.\nGomez JA, Höffner K, Barton PI. BMC Bioinformatics. 2014 Dec 18;15:409."}
+
+[Term]
+id: KISAO_0000503
+name: simulated annealing
+is_a: KISAO_0000472 ! global optimization algorithm
+disjoint_from: KISAO_0000504 ! random search
+property_value: definition "Simulated annealing is an optimization algorithm first proposed by Kirkpatrick et al. and was inspired by statistical mechanics and the way in which perfect crystals are formed. Perfect crystals are formed by first melting the substance of interest, and then cooling it very slowly. At large temperatures the particles vibrate with wide amplitude and this allows a search for global optimum. As the temperature decreases so do the vibrations until the system settles to the global optimum (the perfect crystal).\n\nThe simulated annealing optimization algorithm uses a similar concept: the objective function is considered a measure of the energy of the system and this is maintained constant for a certain number of iterations (a temperature cycle). In each iteration, the parameters are changed to a nearby location in parameter space and the new objective function value calculated; if it decreased, then the new state is accepted, if it increased then the new state is accepted with a probability that follows a Boltzmann distribution (higher temperature means higher probability of accepting the new state). After a fixed number of iterations, the stopping criterion is checked; if it is not time to stop, then the system's temperature is reduced and the algorithm continues.\n\nSimulated annealing is a stochastic algorithm that is guaranteed to converge if ran for an infinite number of iterations. It is one of the most robust global optimization algorithms, although it is also one of the slowest. (Be warned that simulated annealing can run for hours or even days!)." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: seeAlso "http://identifiers.org/doi/10.1126/science.220.4598.671" xsd:anyURI {comment="S. Kirkpatrick, J., C.D. Gelatt, and M. P. Vecchi. Optimization by simulated annealing. Science. 220. 671 - 680. 1983."}
+
+[Term]
+id: KISAO_0000504
+name: random search
+is_a: KISAO_0000472 ! global optimization algorithm
+property_value: definition "Random search is an optimization method that attempts to find the optimum by testing the objective function's value on a series of combinations of random values of the adjustable parameters. The random values are generated complying with any boundaries selected by the user, furthermore, any combinations of parameter values that do not fulfill constraints on the variables are excluded. This means that the method is capable of handling bounds on the adjustable parameters and fulfilling constraints.\n\nFor infinite number of iterations this method is guaranteed to find the global optimum of the objective function. In general one is interested in processing a very large number of iterations." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+
+[Term]
+id: KISAO_0000505
+name: particle swarm
+is_a: KISAO_0000472 ! global optimization algorithm
+property_value: definition "The particle swarm optimization method suggested by Kennedy and Eberhart is inspired by a flock of birds or a school of fish searching for food. Each particle has a position Xi and a velocity Vi in the parameter space. Additionally, it remembers its best achieved objective value O and position Mi. Dependent on its own information and the position of its best neighbor (a random subset of particles of the swarm) a new velocity is calculated. With this information the position is updated." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: seeAlso "http://identifiers.org/doi/10.1109/ICNN.1995.488968" xsd:anyURI {comment="J. Kennedy and R. Eberhart. Particle Swarm Optimization. Proceedings of the Fourth IEEE International Conference on Neural Networks, Perth, Australia. 1942 - 1948. 1995."}
+
+[Term]
+id: KISAO_0000506
+name: genetic algorithm
+is_a: KISAO_0000520 ! evolutionary algorithm
+disjoint_from: KISAO_0000508 ! evolutionary programming
+property_value: altLabel "GA" xsd:string
+property_value: definition "The genetic algorithm (GA) is a computational technique that mimics evolution and is based on reproduction and selection. A GA is composed of individuals that reproduce and compete, each one is a potential solution to the (optimization) problem and is represented by a \"genome\" where each gene corresponds to one adjustable parameter. At each generation of the GA, each individual is paired with one other at random for reproduction. Two offspring are produced by combining their genomes and allowing for \"cross-over\", i.e., the two new individuals have genomes that are formed from a combination of the genomes of their parents. Also each new gene might have mutated, i.e. the parameter value might have changed slightly. At the end of the generation, the algorithm has double the number of individuals. Then each of the individuals is confronted with a number of others to count how many does it outperform (the number of wins is the number of these competitors that represent worse solutions than itself). All the individuals are ranked by their number of wins, and the population is again reduced to the original number of individuals by eliminating those which have worse fitness (solutions)." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: seeAlso "http://identifiers.org/isbn/9780750308953" xsd:anyURI {comment="T. Bäck, D.B. Fogel, and Z. Michalewicz. Handbook of evolutionary computation. Oxford: IOP Publishing/Oxford University Press. 1997."}
+
+[Term]
+id: KISAO_0000507
+name: genetic algorithm SR
+is_a: KISAO_0000506 ! genetic algorithm
+property_value: altLabel "genetic algorithm with stochastic ranking" xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: seeAlso "http://identifiers.org/doi/10.1109/4235.873238" xsd:anyURI {comment="T. Runarsson and X. Yao. Stochastic ranking for constrained evolutionary optimization. EEE Transactions on Evolutionary Computation. 4. 284 - 294. 2000."}
+
+[Term]
+id: KISAO_0000508
+name: evolutionary programming
+is_a: KISAO_0000520 ! evolutionary algorithm
+property_value: altLabel "EP" xsd:string
+property_value: definition "Evolutionary programming (EP) is a computational technique that mimics evolution and is based on reproduction and selection. An EP algorithm is composed of individuals that reproduce and compete, each one is a potential solution to the (optimization) problem and is represented by a \"genome\" where each gene corresponds to one adjustable parameter. At each generation of the EP, each individual reproduces asexually, i.e. divides into two individuals. One of these contains exactly the same \"genome\" as the parent while the other suffers some mutations (the parameter values of each gene change slightly). At the end of the generation, the algorithm has double the number of individuals. Then each of the individuals is confronted with a number of others to count how many does it outperform (the number of wins is the number of these competitors that represent worse solutions than itself). All the individuals are ranked by their number of wins, and the population is again reduced to the original number of individuals by eliminating those which have worse fitness (solutions)." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: seeAlso "http://identifiers.org/isbn/9780750308953" xsd:anyURI {comment="T. Bäck, D.B. Fogel, and Z. Michalewicz. Handbook of evolutionary computation. Oxford: IOP Publishing/Oxford University Press. 1997."}
+
+[Term]
+id: KISAO_0000509
+name: evolutionary strategy
+is_a: KISAO_0000508 ! evolutionary programming
+property_value: altLabel "evolutionary strategies with stochastic ranking" xsd:string
+property_value: altLabel "SRES" xsd:string
+property_value: definition "Evolutionary Strategies with Stochastic Ranking (SRES) is similar to Evolutionary Programming. However, a parent has multiple offsprings during each generation. Each offspring will contain a recombination of genes with another parent and additional mutations. The algorithm assures that each parameter value will be within its boundaries. But constraints to the solutions may be violated." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: seeAlso "http://identifiers.org/doi/10.1109/4235.873238" xsd:anyURI {comment="T. Runarsson and X. Yao. Stochastic ranking for constrained evolutionary optimization. EEE Transactions on Evolutionary Computation. 4. 284 - 294. 2000."}
+
+[Term]
+id: KISAO_0000510
+name: truncated Newton
+is_a: KISAO_0000471 ! local optimization algorithm
+disjoint_from: KISAO_0000511 ! steepest descent
+property_value: definition "The Truncated Newton method is a sophisticated variant of the Newton optimization method. The Newton optimization method searches for the minimum of a nonlinear function by following descent directions determined from the function's first and second partial derivatives. The Truncated Newton method does an incomplete (truncated) solution of a system of linear equations to calculate the Newton direction. This means that the actual direction chosen for the descent is between the steepest descent direction and the true Newton direction." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: seeAlso "http://identifiers.org/isbn/0122839528" xsd:anyURI {comment="P.E. Gill, W. Murray, and M.H. Wright. Practical Optimization. London, Academic Press. 1981."}
+
+[Term]
+id: KISAO_0000511
+name: steepest descent
+is_a: KISAO_0000471 ! local optimization algorithm
+property_value: definition "Steepest descent is an optimization method that follows the direction of steepest descent on the hyper-surface of the objective function to find a local minimum. The direction of steepest descent is defined by the negative of the gradient of the objective function." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1109/ACSSC.1991.186507" xsd:anyURI {comment="D.B. Fogel, L.J. Fogel, and J.W. Atmar. Meta-evolutionary programming. 25th Asiloma Conference on Signals, Systems and Computers. IEEE Computer Society, Asilomar . 540 - 545. 1992."}
+
+[Term]
+id: KISAO_0000512
+name: praxis
+is_a: KISAO_0000471 ! local optimization algorithm
+property_value: definition "Praxis is a direct search method that searches for the minimum of a nonlinear function without requiring (or attempting to calculate) derivatives of that function. Praxis was developed by Brent after the method proposed by Powell. The inspiration for Praxis was the well-known method of minimising each adjustable parameter (direction) at a time - the principal axes method. In Praxis directions are chosen that do not coincide with the principal axes, in fact if the objective function is quadratic then these will be conjugate directions, assuring a fast convergence rate." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: seeAlso "http://identifiers.org/isbn/0486419983" xsd:anyURI {comment="P.R. Brent. A new algorithm for minimizing a function of several variables without calculating derivatives. In Algorithms for minimization without derivatives, (Englewood Cliffs, NJ: Prentice-Hall, Inc.). 117 - 167. 1973."}
+
+[Term]
+id: KISAO_0000513
+name: NL2SOL
+is_a: KISAO_0000471 ! local optimization algorithm
+property_value: altLabel "adaptive nonlinear least-squares algorithm" xsd:string
+property_value: definition "The NL2SOL method is based on an adaptive nonlinear least-squares algorithm, devised by Dennis and colleagues. For problems with large number of residuals, this algorithm is known to be more reliable than Gauss-Newton or Levenberg-Marquardt method and more efficient than the secant or variable metric algorithms that are intended for general function minimization." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: seeAlso "http://identifiers.org/doi/10.1145/355958.355966" xsd:anyURI {comment="J. E. Dennis, D. M. Gay, and R. E. Welsch. An adaptive nonlinear least-squares algorithm. ACM Trans. Math. Softw.. 7(3). 348 - 368. 1981."}
+
+[Term]
+id: KISAO_0000514
+name: Nelder-Mead
+is_a: KISAO_0000471 ! local optimization algorithm
+property_value: altLabel "simplex method" xsd:string
+property_value: definition "This method also known as the simplex method is due to Nelder and Mead. A simplex is a polytope of N+1 vertices in N dimensions. The objective function is evaluated at each vertex. Dependent on these calculated values a new simplex is constructed. The simplest step is to replace the worst point with a point reflected through the centroid of the remaining N points. If this point is better than the best current point, then we can try stretching exponentially out along this line. On the other hand, if this new point isn't much better than the previous value then we are stepping across a valley, so we shrink the simplex towards the best point." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: seeAlso "http://identifiers.org/doi/10.1093/comjnl/7.4.308" xsd:anyURI {comment="J. A. Nelder and R. Mead. A simplex method for function minimization. Computer Journal. 7. 308 - 313. 1965."}
+
+[Term]
+id: KISAO_0000515
+name: Levenberg-Marquardt
+is_a: KISAO_0000471 ! local optimization algorithm
+property_value: definition "Levenberg-Marquardt is a gradient descent method. It is a hybrid between the steepest descent and the Newton methods.\nLevenberg first suggested an improvement to the Newton method in order to make it more robust, i.e. to overcome the problem of non-convergence. His suggestion was to add a factor to the diagonal elements of the Hessian matrix of second derivatives when not close to the minimum (this can be judged by how positive definite the matrix is). The effect when this factor is large compared to the elements of Hessian is that the method then becomes the steepest descent method. Later Marquardt suggested that the factor should be multiplicative rather than additive and also defined a heuristic to make this factor increase or decrease. The method known as Levenberg-Marquardt is thus an adaptive method that effectively changes between the steepest descent to the Newton method." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: seeAlso "http://identifiers.org/doi/10.1090/qam/10666" xsd:anyURI {comment="K. Levenberg. A method for the solution of certain nonlinear problems in least squares. Quart. Appl. Math.. 2. 164 - 168. 1944."}
+property_value: seeAlso "http://identifiers.org/doi/10.1137/0111030" xsd:anyURI {comment="D.W. Marquardt. An algorithm for least squares estimation of nonlinear parameters. SIAM Journal. 11. 431 - 441. 1963."}
+
+[Term]
+id: KISAO_0000516
+name: Hooke&Jeeves
+is_a: KISAO_0000471 ! local optimization algorithm
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+property_value: altLabel "Hooke-Jeeves method" xsd:string
+property_value: altLabel "method of Hooke and Jeeves" xsd:string
+property_value: definition "The method of Hooke and Jeeves is a direct search algorithm that searches for the minimum of a nonlinear function without requiring (or attempting to calculate) derivatives of the function. Instead it is based on a heuristic that suggests a descent direction using the values of the function calculated in a number of previous iterations." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: seeAlso "http://identifiers.org/doi/10.1145/321062.321069" xsd:anyURI {comment="R. Hooke and T. A. Jeeves. \"Direct search\" solution of numerical and statistical problems. Journal of the Association for Computing Machinery. 8. 212 - 229. 1961."}
+
+[Term]
+id: KISAO_0000520
+name: evolutionary algorithm
+is_a: KISAO_0000472 ! global optimization algorithm
+property_value: definition "An optimisation algorithm that mimics evolution and is based on reproduction and selection." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isOrganizational "true" xsd:string
+
+[Term]
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+name: partitioned leaping method
+is_a: KISAO_0000039 ! tau-leaping method
+property_value: definition "Multiscale simulation approach for modeling stochasticity in chemical reaction networks. The approach seamlessly integrates exact-stochastic and \"leaping\" methodologies into a single partitioned leaping algorithmic framework. The technique correctly accounts for stochastic noise at significantly reduced computational cost, requires the definition of only three modelindependent parameters and is particularly well-suited for simulating systems containing widely disparate species populations." xsd:string
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+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2354085" xsd:anyURI {comment="Harris LA, Clancy P. A \"partitioned leaping\" approach for multiscale modeling of chemical reaction dynamics. J Chem Phys. 125 (14), 144107 (2006)."}
+
+[Term]
+id: KISAO_0000526
+name: flux variability analysis
+is_a: KISAO_0000407 ! steady state method
+is_a: KISAO_0000622 ! flux balance method
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+property_value: definition "Method for determining the minimum and maximum flux of each reaction that satisfies the flux constraints of the flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/cobrapy" xsd:anyURI {comment="COBRApy"}
+property_value: seeAlso "http://identifiers.org/doi/10.1016/j.ymben.2003.09.002" xsd:anyURI {comment="Mahadevan R, Schilling CH. The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. Metab Eng. 2003;5(4):264-276."}
+
+[Term]
+id: KISAO_0000527
+name: geometric flux balance analysis
+is_a: KISAO_0000437 ! flux balance analysis
+disjoint_from: KISAO_0000591 ! mdFBA
+property_value: altLabel "geometric FBA" xsd:string
+property_value: altLabel "gFBA" xsd:string
+property_value: definition "Method for determining the central flux distribution among all flux distributions that satisfy the constraints of the  flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/cobrapy" xsd:anyURI {comment="COBRApy"}
+property_value: seeAlso "http://identifiers.org/doi/10.1016/j.jtbi.2009.01.027" xsd:anyURI {comment="Smallbone K, Simeonidis E. Flux balance analysis: a geometric perspective. J Theor Biol. 2009;258(2):311-315."}
+
+[Term]
+id: KISAO_0000528
+name: parsimonious enzyme usage flux balance analysis (minimum sum of absolute fluxes)
+is_a: KISAO_0000620 ! parsimonius flux balance analysis
+disjoint_from: KISAO_0000554 ! parsimonius flux balance analysis (minimum number of active fluxes)
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+property_value: altLabel "parsimonious flux balance analysis" xsd:string
+property_value: altLabel "pFBA" xsd:string
+property_value: definition "Method for determining the smallest flux distribution among all flux distributions that satisfy the constraints of the flux balance analysis (FBA) [http://identifiers.org/biomodels.kisao/KISAO_0000437] model." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
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+property_value: seeAlso "http://identifiers.org/doi/10.1038/msb.2010.47" xsd:anyURI {comment="Lewis NE, Hixson KK, Conrad TM, et al. Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models. Mol Syst Biol. 2010;6:390."}
+
+[Term]
+id: KISAO_0000535
+name: VODE
+is_a: KISAO_0000433 ! CVODE-like method
+relationship: KISAO_0000359 KISAO_0000019 {maxCardinality="1"} ! CVODE
+property_value: altLabel "DVODE" xsd:string {comment="RELATED"}
+property_value: altLabel "Real-valued Variable-coefficient Ordinary Differential Equation solver, with fixed-leading-coefficient implementation" xsd:string {comment="EXACT"}
+property_value: altLabel "real-valued variable-coefficient ordinary differential equation solver, with fixed-leading-coefficient implementation" xsd:string
+property_value: definition "VODE provides implicit Adams method (for non-stiff problems) and a method based on backward differentiation formulas (BDF) (for stiff problems)." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "deSolve" xsd:string
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+property_value: seeAlso "http://identifiers.org/doi/10.1137/0910062" xsd:anyURI {comment="Peter N. Brown, George D. Byrne & Alan C. Hindmarsh. VODE: A Variable-Coefficient ODE Solver. SIAM J. Sci. and Stat. Comput., 10(5), 1038–1051 (1988)."}
+
+[Term]
+id: KISAO_0000536
+name: ZVODE
+is_a: KISAO_0000433 ! CVODE-like method
+relationship: KISAO_0000359 KISAO_0000019 {maxCardinality="1"} ! CVODE
+property_value: altLabel "Complex-valued Variable-coefficient Ordinary Differential Equation solver, with fixed-leading-coefficient implementation" xsd:string {comment="EXACT"}
+property_value: altLabel "complex-valued variable-coefficient ordinary differential equation solver, with fixed-leading-coefficient implementation" xsd:string
+property_value: definition "ZVODE provides implicit Adams method (for non-stiff problems) and a method based on backward differentiation formulas (BDF) (for stiff problems)." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "deSolve" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
+property_value: isImplementedIn "Odespy" xsd:string
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+property_value: seeAlso "http://identifiers.org/doi/10.1137/0910062" xsd:anyURI {comment="Peter N. Brown, George D. Byrne & Alan C. Hindmarsh. VODE: A Variable-Coefficient ODE Solver. SIAM J. Sci. and Stat. Comput., 10(5), 1038–1051 (1988)."}
+
+[Term]
+id: KISAO_0000537
+name: explicit Runge-Kutta method of order 3(2)
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: altLabel "RK23" xsd:string {comment="EXACT"}
+property_value: definition "RK23 uses the Bogacki-Shampine pair of formulas [1]. The error is controlled assuming accuracy of the second-order method, but steps are taken using the third-order accurate formula (local extrapolation is done). A cubic Hermite polynomial is used for the dense output." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "deSolve" xsd:string
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+property_value: seeAlso "http://identifiers.org/doi/10.1016/0893-9659(89)90079-7" xsd:anyURI {comment="P. Bogacki & L. F. Shampine. A 3(2) pair of Runge - Kutta formulas. Applied Mathematics Letters 2(4), 321-325 (1989)."}
+
+[Term]
+id: KISAO_0000544
+name: IDAS
+is_a: KISAO_0000432 ! IDA-like method
+property_value: altLabel "implicit differential-algebraic solver with sensitivity analysis" xsd:string {comment="EXACT"}
+property_value: definition "IDAS solves real differential-algebraic systems in N-space, in the general form F(t,y,y')=0, y(t0)=y0, y'(t0)=y'0 with sensitivity analysis." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
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+
+[Term]
+id: KISAO_0000546
+name: convex optimization algorithm
+is_a: KISAO_0000472 ! global optimization algorithm
+property_value: definition "Optimization of a convex function over a convex set. Convex optimization is subclass of global optimization because conveness gaurantees that each local optimum is a global optimum." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+
+[Term]
+id: KISAO_0000547
+name: linear programming
+is_a: KISAO_0000546 ! convex optimization algorithm
+property_value: altLabel "LP" xsd:string {comment="EXACT"}
+property_value: definition "Method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
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+property_value: isImplementedIn "XPRESS" xsd:string
+
+[Term]
+id: KISAO_0000548
+name: quadratic programming
+is_a: KISAO_0000549 ! non-linear programming
+property_value: altLabel "QP" xsd:string {comment="EXACT"}
+property_value: definition "Process of solving a quadratic optimization problem." xsd:string
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+
+[Term]
+id: KISAO_0000549
+name: non-linear programming
+is_a: KISAO_0000472 ! global optimization algorithm
+property_value: definition "Process of solving an optimization problem where some of the constraints or the objective function are nonlinear." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+
+[Term]
+id: KISAO_0000550
+name: simplex method
+is_a: KISAO_0000547 ! linear programming
+property_value: altLabel "Dantzig's simplex algorithm" xsd:string {comment="EXACT"}
+property_value: definition "Approach to solving linear programming models by hand using slack variables, tableaus, and pivot variables as a means to finding the optimal solution of an optimization problem." xsd:string
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+property_value: seeAlso "https://projecteuclid.org/euclid.pjm/1103044531" xsd:anyURI
+
+[Term]
+id: KISAO_0000551
+name: primal-dual interior point method
+is_a: KISAO_0000547 ! linear programming
+property_value: definition "The Interior Point method approximates the constraints of a linear programming model as a set of boundaries surrounding a region." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "CPLEX" xsd:string
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+property_value: seeAlso "http://identifiers.org/doi/10.1137/0802028" xsd:anyURI {comment="Sanjay Mehrotra. On the Implementation of a Primal-Dual Interior Point Method. SIAM Journal on Optimization, 2(4), 575–601(1991)."}
+
+[Term]
+id: KISAO_0000554
+name: parsimonius flux balance analysis (minimum number of active fluxes)
+is_a: KISAO_0000620 ! parsimonius flux balance analysis
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+property_value: altLabel "parsimonious flux balance analysis" xsd:string
+property_value: altLabel "pFBA" xsd:string
+property_value: definition "A technique for selecting a parsimonious flux distribution which has a minimal number of active fluxes." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/cbmpy" xsd:anyURI {comment="CBMPy"}
+
+[Term]
+id: KISAO_0000560
+name: LSODA/LSODAR hybrid method
+is_a: KISAO_0000094 ! Livermore solver
+property_value: definition "Automatically use LSODA or LSODAR as apropriate for the given problem. Use LSODA if the problem has no roots. Use LSODAR if the problem has roots." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
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+
+[Term]
+id: KISAO_0000561
+name: Pahle hybrid Gibson-Bruck Next Reaction method/Runge-Kutta method
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+property_value: definition "Combines a deterministic numerical integration of ODEs with a stochastic simulation algorithm. The whole biochemical network is partitioned into a deterministic and a stochastic subnet internally. The deterministic subnet contains all reactions in which only species with high particle numbers take part. All reactions with at least one low-numbered species are in the stochastic subnet. The partitioning of the biochemical network can change dynamically during the simulation. The reaction probabilities of the stochastic subnet are approximated as constant during one stochastic step. A 4th-order Runge-Kutta method is used to numerically integrate the deterministic part of the system. The stochastic subnet is simulated by the Gibson-Bruck Next Reaction Method." xsd:string
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+
+[Term]
+id: KISAO_0000562
+name: Pahle hybrid Gibson-Bruck Next Reaction method/LSODA method
+is_a: KISAO_0000231 ! Pahle hybrid method
+property_value: definition "Combines a deterministic numerical integration of ODEs with a stochastic simulation algorithm. The whole biochemical network is partitioned into a deterministic and a stochastic subnet internally. The deterministic subnet contains all reactions in which only species with high particle numbers take part. All reactions with at least one low-numbered species are in the stochastic subnet. The partitioning of the biochemical network can change dynamically during the simulation. The reaction probabilities of the stochastic subnet are approximated as constant during one stochastic step. The deterministic subnet is integrated with LSODA. The stochastic subnet is simulated by the Gibson-Bruck Next Reaction Method." xsd:string
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+property_value: seeAlso "http://identifiers.org/doi/10.1016/j.jbiotec.2017.06.1200" xsd:anyURI {comment="Frank T. Bergmann, Stefan Hoops, Brian Klahn, Ursula Kummer, Pedro Mendes Jürgen Pahle & Sven Sahle. COPASI and its applications in biotechnology. Journal of Biotechnology 261, 215–220 (2017)."}
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+
+[Term]
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+name: Pahle hybrid Gibson-Bruck Next Reaction method/RK-45 method
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+property_value: seeAlso "http://identifiers.org/doi/10.1007/978-1-59745-525-1_2" xsd:anyURI {comment="Pedro Mendes, Stefan Hoops, Sven Sahle, Ralph Gauges, Joseph Dada & Ursula Kummer. Computational modeling of biochemical networks using COPASI. Methods in Molecular Biology 500, 17–59 (2009)."}
+property_value: seeAlso "http://identifiers.org/doi/10.1016/j.jbiotec.2017.06.1200" xsd:anyURI {comment="Frank T. Bergmann, Stefan Hoops, Brian Klahn, Ursula Kummer, Pedro Mendes Jürgen Pahle & Sven Sahle. COPASI and its applications in biotechnology. Journal of Biotechnology 261, 215–220 (2017)."}
+property_value: seeAlso "http://identifiers.org/doi/10.1093/bioinformatics/btl485" xsd:anyURI {comment="Stefan Hoops, Sven Sahle, Ralph Gauges, Christine Lee, Jürgen Pahle, Natalia Simus, Mudita Singhal, Liang Xu, Pedro Mendes & Ursula Kummer. COPASI—a complex pathway simulator. Bioinformatics 22 (24), 3067–3074 (2006)."}
+property_value: seeAlso "http://identifiers.org/doi/10.5555/1218112.1218421" xsd:anyURI {comment="Sven Sahle, Ralph Gauges, Jürgen Pahle, Natalia Simus, Ursula Kummer, Stefan Hoops, Christine Lee, Mudita Singhal, Liang Xu & Pedro Mendes. Simulation of biochemical networks using COPASI—a complex pathway simulator. Proceedings of the 2006 Winter Simulation Conference, Monterey, CA, USA, 1698–1706 (2006)."}
+
+[Term]
+id: KISAO_0000564
+name: stochastic Runge-Kutta method
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: definition "Technique for the approximate numerical solution of a systems of stochastic differential equations (SDEs). The method is a generalisation of the Runge-Kutta method for ordinary differential equations to stochastic differential equations." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: seeAlso "https://en.wikipedia.org/wiki/Runge%E2%80%93Kutta_method_(SDE)" xsd:anyURI
+
+[Term]
+id: KISAO_0000566
+name: stochastic second order Runge-Kutta method
+is_a: KISAO_0000564 ! stochastic Runge-Kutta method
+property_value: altLabel "RI5" xsd:string {comment="EXACT"}
+property_value: definition "Technique for the second order approximate numerical solution of a systems of stochastic differential equations (SDEs). The method is a generalisation of the Runge-Kutta method for ordinary differential equations to stochastic differential equations." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/copasi" xsd:anyURI {comment="COPASI"}
+property_value: seeAlso "http://identifiers.org/doi/10.1137/060673308" xsd:anyURI {comment="Andreas Rößler. Second order Runge-Kutta methods for Itô stochastic differential equations. SIAM Journal Numerical Analysis 47 (3), 1713–1738 (2009)."}
+
+[Term]
+id: KISAO_0000568
+name: NLEQ1
+is_a: KISAO_0000408 ! Newton-type method
+property_value: altLabel "Newton-type method for solveing non-linear (NL) equations (EQ)" xsd:string
+property_value: altLabel "numerical solution of nonlinear (NL) equations (EQ) especially designed for numerically sensitive problems" xsd:string
+property_value: definition "Damped Newton-algorithm with rank strategy for systems of highly nonlinear equations.\n\nGlobal Newton method with error oriented convergence criterion; arbitrary selection of direct linear equation solver." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: seeAlso "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.3751" xsd:anyURI {comment="Ulrich Nowak & Lutz Weimann. A family of Newton codes for systems of highly nonlinear equations - algorithm, implementation, application. Konrad-Zuse-Zentrum für Informationstechnik Berlin 91-10 (1991)."}
+property_value: seeAlso "http://identifiers.org/doi/10.1007/978-3-642-23899-4" xsd:anyURI {comment="Peter Deuflhard. Newton methods for nonlinear problems. Affine Invariance and Adaptive Algorithms (2004)."}
+
+[Term]
+id: KISAO_0000569
+name: NLEQ2
+is_a: KISAO_0000408 ! Newton-type method
+property_value: altLabel "Newton-type method for solveing non-linear (NL) equations (EQ)" xsd:string
+property_value: altLabel "numerical solution of nonlinear (NL) equations (EQ) especially designed for numerically sensitive problems" xsd:string
+property_value: definition "Damped Newton-algorithm with rank strategy for systems of highly nonlinear equations.\n\nGlobal Newton method with error oriented convergence criterion; QR-decomposition with subcondition number estimate." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/tellurium" xsd:anyURI {comment="tellurium"}
+property_value: seeAlso "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.3751" xsd:anyURI {comment="Ulrich Nowak & Lutz Weimann. A family of Newton codes for systems of highly nonlinear equations - algorithm, implementation, application. Konrad-Zuse-Zentrum für Informationstechnik Berlin 91-10 (1991)."}
+property_value: seeAlso "http://identifiers.org/doi/10.1007/978-3-642-23899-4" xsd:anyURI {comment="Peter Deuflhard. Newton methods for nonlinear problems. Affine Invariance and Adaptive Algorithms (2004)."}
+
+[Term]
+id: KISAO_0000573
+name: probabilistic logical model simulation method
+is_a: KISAO_0000319 ! Monte Carlo method
+is_a: KISAO_0000448 ! logical model simulation method
+property_value: definition "Qualitative (logical) models specify the evolution rules of their components. Probabilistic networks allow for specifying more than one transition function per variable/gene. Each of these functions has a probability to be chosen, where the probabilities of all functions for one variable sum up to 1. Transitions are performed synchronously by choosing one transition function for each gene according to their probabilities and applying them to the current state." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/boolnet" xsd:anyURI {comment="BoolNet"}
+property_value: seeAlso "http://identifiers.org/doi/10.1093/bioinformatics/btq124" xsd:anyURI
+
+[Term]
+id: KISAO_0000575
+name: hybrid tau-leaping method
+is_a: KISAO_0000039 ! tau-leaping method
+is_a: KISAO_0000352 ! hybrid method
+property_value: definition "A continuously coupled hybrid deterministic/stochastic simulation algorithm for biochemical networks. Biochemical species are classified as continuous, discrete, or switch. Tau-leaping is used to simulate stochastic species, and LSODA or another ODE integration method is used to simulate continuous species. Switch species are dynamically classified as either continuous or discrete at each timestep depending on a user defined error tolerance." xsd:string
+property_value: http://purl.org/dc/terms/creator "BD" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/gillespy2" xsd:anyURI {comment="GillesPy2"}
+property_value: seeAlso "https://github.com/StochSS/GillesPy2" xsd:anyURI {comment="Drawert B et al. GillesPy2"}
+
+[Term]
+id: KISAO_0000576
+name: quadratic MOMA
+is_a: KISAO_0000593 ! MOMA
+disjoint_from: KISAO_0000579 ! linear MOMA
+property_value: altLabel "minimization of metabolic adjustment" xsd:string
+property_value: altLabel "MOMA" xsd:string
+property_value: altLabel "Quadratic Minimization of Metabolic Adjustment" xsd:string {comment="EXACT"}
+property_value: altLabel "quadratic minimization of metabolic adjustment" xsd:string
+property_value: definition "Minimization of metabolic adjustment (MOMA) is an extension of FBA for the prediction of flux distributions in gene knockouts. MOMA employs quadratic programming to identify the closest point (in terms of its Euclidean distance) in the permissible flux space of the knockout to the wild-type flux vector by solving the optimization problem\n\nMin sum((fluxAi - fluxBi)^2) + sum(fluxAi)^(fluxMinimizationWeight) + sum(fluxBi)^(fluxMinimizationWeight)" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/optflux" xsd:anyURI {comment="Optflux"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/raven" xsd:anyURI {comment="RAVEN"}
+property_value: seeAlso "http://identifiers.org/doi/10.1073/pnas.232349399" xsd:anyURI {comment="Segre, D., Vitkup, D., & Church, G. M. (2002). Analysis of optimality in natural and perturbed metabolic networks. Proceedings of the National Academy of Sciences, 99(23), 15112-15117."}
+
+[Term]
+id: KISAO_0000579
+name: linear MOMA
+is_a: KISAO_0000593 ! MOMA
+property_value: altLabel "Linear Minimization of Metabolic Adjustment" xsd:string {comment="EXACT"}
+property_value: altLabel "linear minimization of metabolic adjustment" xsd:string
+property_value: definition "Linear minimization of metabolic adjustment (MOMA) is an extension of FBA for the prediction of flux distributions in gene knockouts. Linear MOMA employs linear programming to identify the closest point (in terms of its L1 norm) in the permissible flux space of the knockout to the wild-type flux vector by solving the optimization problem\n\nMin sum(|fluxAi - fluxBi|)" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/optflux" xsd:anyURI {comment="Optflux"}
+property_value: seeAlso "http://identifiers.org/doi/10.1038/ng.846" xsd:anyURI {comment="Szappanos, B., Kovács, K., Szamecz, B., Honti, F., Costanzo, M., Baryshnikova, A., ... & Andrews, B. J. (2011). An integrated approach to characterize genetic interaction networks in yeast metabolism. Nature genetics, 43(7), 656-662."}
+
+[Term]
+id: KISAO_0000580
+name: ROOM
+is_a: KISAO_0000407 ! steady state method
+is_a: KISAO_0000622 ! flux balance method
+property_value: altLabel "Regulatory on/off minimization of metabolic flux changes" xsd:string {comment="EXACT"}
+property_value: altLabel "regulatory on/off minimization of metabolic flux changes" xsd:string
+property_value: definition "Constraint-based algorithm for predicting the metabolic steady state after gene knockouts which aims to minimize the number of significant flux changes (hence on/off) with respect to the wild type." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/optflux" xsd:anyURI {comment="Optflux"}
+property_value: seeAlso "http://identifiers.org/doi/10.1073/pnas.0406346102" xsd:anyURI {comment="Shlomi, T., Berkman, O., & Ruppin, E. (2005). Regulatory on/off minimization of metabolic flux changes after genetic perturbations. Proceedings of the national academy of sciences, 102(21), 7695-7700."}
+
+[Term]
+id: KISAO_0000581
+name: BKMC
+is_a: KISAO_0000319 ! Monte Carlo method
+is_a: KISAO_0000573 ! probabilistic logical model simulation method
+relationship: KISAO_0000359 KISAO_0000029 ! Gillespie direct algorithm
+property_value: altLabel "Boolean Kinetic Monte-Carlo" xsd:string {comment="EXACT"}
+property_value: altLabel "Boolean kinetic Monte-Carlo" xsd:string
+property_value: definition "The Boolean kinetic Monte Carlo method (BKMC) is a natural generalization of the asynchronous Boolean simulation method, with a direct probabilistic interpretation. In the BKMC framework, the dynamics is parameterized by a biological time and the order of update is noisy, which is less strict than priority classes introduced in GINsin. A BKMC model is specified by logical rules as in regular Boolean models but with a more precise information: a numerical rate is added for each transition of each node." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/maboss" xsd:anyURI {comment="MaBoSS"}
+property_value: seeAlso "http://identifiers.org/doi/10.1186/1752-0509-6-116" xsd:anyURI {comment="Stoll, G., Viara, E., Barillot, E., & Calzone, L. (2012). Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm. BMC systems biology, 6(1), 1-18."}
+
+[Term]
+id: KISAO_0000582
+name: Spatiocyte method
+is_a: KISAO_0000056 ! Smoluchowski equation based method
+property_value: definition "Lattice-based stochastic particle simulation method for biochemical reaction and diffusion processes." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ecell4" xsd:anyURI {comment="E-Cell 4"}
+property_value: seeAlso "http://identifiers.org/doi/10.1038/npre.2009.3845.1" xsd:anyURI {comment="Arjunan, S., & Tomita, M. (2009). A new multicompartmental reaction-diffusion modeling method links transient membrane attachment of E. coli MinE to E-ring formation. Nature Precedings, 1-1."}
+
+[Term]
+id: KISAO_0000585
+name: TOMS731
+is_a: KISAO_0000369 ! partial differential equation discretization method
+property_value: definition "Moving-grid interface for systems of one-dimensional time-dependent partial differential equations." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/jsim" xsd:anyURI {comment="JSim"}
+property_value: seeAlso "http://identifiers.org/doi/10.1145/178365.178391" xsd:anyURI {comment="Blom, J. G., & Zegeling, P. A. (1994). Algorithm 731: a moving-grid interface for systems of one-dimensional time-dependent partial differential equations. ACM Transactions on Mathematical Software (TOMS), 20(2), 194-214."}
+
+[Term]
+id: KISAO_0000586
+name: Gibson-Bruck next reaction algorithm with indexed priority queue
+is_a: KISAO_0000027 ! Gibson-Bruck next reaction algorithm
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/sbscl" xsd:anyURI {comment="SBSCL"}
+
+[Term]
+id: KISAO_0000587
+name: IMEX
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: altLabel "Implicit-Explicit Runge-Kutta method" xsd:string {comment="EXACT"}
+property_value: altLabel "implicit-explicit Runge-Kutta method" xsd:string
+property_value: definition "Method for solving stiff and imaginary ODE problems" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/biouml" xsd:anyURI {comment="BioUML"}
+
+[Term]
+id: KISAO_0000588
+name: flux sampling
+is_a: KISAO_0000407 ! steady state method
+property_value: definition "Method for sampling fluxes from the null space of a flux balance analysis model" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000589
+name: ACB flux sampling method
+is_a: KISAO_0000588 ! flux sampling
+disjoint_from: KISAO_0000590 ! ACHR flux sampling method
+property_value: altLabel "Artificial centering boundary flux sampling method" xsd:string {comment="EXACT"}
+property_value: altLabel "artificial centering boundary flux sampling method" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+property_value: seeAlso "http://identifiers.org/doi/10.1038/s41596-018-0098-2" xsd:anyURI {comment="Heirendt, L., Arreckx, S., Pfau, T., Mendoza, S. N., Richelle, A., Heinken, A., ... & Magnusdóttir, S. (2019). Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v. 3.0. Nature protocols, 14(3), 639-702."}
+
+[Term]
+id: KISAO_0000590
+name: ACHR flux sampling method
+is_a: KISAO_0000588 ! flux sampling
+property_value: altLabel "artificial centering hit-and-run flux sampling method" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/cobrapy" xsd:anyURI {comment="COBRApy"}
+property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+property_value: seeAlso "http://identifiers.org/doi/10.1287/opre.46.1.84" xsd:anyURI {comment="Kaufman, D. E., & Smith, R. L. (1998). Direction choice for accelerated convergence in hit-and-run sampling. Operations Research, 46(1), 84-95."}
+
+[Term]
+id: KISAO_0000591
+name: mdFBA
+is_a: KISAO_0000437 ! flux balance analysis
+property_value: altLabel "metabolic dilution flux balance analysis" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+property_value: seeAlso "http://identifiers.org/doi/10.1186/gb-2010-11-4-r43" xsd:anyURI {comment="Benyamini, T., Folger, O., Ruppin, E., & Shlomi, T. (2010). Flux balance analysis accounting for metabolite dilution. Genome biology, 11(4), R43."}
+
+[Term]
+id: KISAO_0000592
+name: dynamic rFBA
+is_a: KISAO_0000595 ! rFBA
+disjoint_from: KISAO_0000596 ! srFBA
+property_value: altLabel "dynamic regulatory flux balance analysis" xsd:string {comment="EXACT"}
+property_value: altLabel "regulatory flux balance analysis" xsd:string
+property_value: altLabel "rFBA" xsd:string
+property_value: definition "Method for predicting the dynamics of metabolic fluxes under patterns of the regulation of gene expression" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/cobratoolbox" xsd:anyURI {comment="COBRA Toolbox"}
+property_value: seeAlso "http://identifiers.org/doi/10.1006/jtbi.2001.2405" xsd:string {comment="Covert, M. W., Schilling, C. H., & Palsson, B. (2001). Regulation of gene expression in flux balance models of metabolism. Journal of theoretical biology, 213(1), 73-88."}
+
+[Term]
+id: KISAO_0000593
+name: MOMA
+is_a: KISAO_0000407 ! steady state method
+is_a: KISAO_0000622 ! flux balance method
+property_value: altLabel "Minimization of Metabolic Adjustment" xsd:string {comment="EXACT"}
+property_value: altLabel "minimization of metabolic adjustment" xsd:string
+property_value: definition "minimization of metabolic adjustment (MOMA) is an extension of FBA for the prediction of flux distributions in gene knockouts. MOMA identifies the closest point in the permissible flux space of the knockout to the wild-type flux vector by solving an optimization problem." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000595
+name: rFBA
+is_a: KISAO_0000352 ! hybrid method
+is_a: KISAO_0000622 ! flux balance method
+property_value: altLabel "regulatory flux balance analysis" xsd:string {comment="EXACT"}
+property_value: definition "Method for predicting metabolic fluxes under patterns of the regulation of gene expression" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000596
+name: srFBA
+is_a: KISAO_0000437 ! flux balance analysis
+is_a: KISAO_0000595 ! rFBA
+property_value: altLabel "SR-FBA" xsd:string {comment="EXACT"}
+property_value: altLabel "steady-state regulatory flux balance analysis" xsd:string
+property_value: definition "Method for predicting steady-state metabolic fluxes under patterns of the regulation of gene expression" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1038/msb4100141" xsd:string {comment="Shlomi, T., Eisenberg, Y., Sharan, R., & Ruppin, E. (2007). A genome‐scale computational study of the interplay between transcriptional regulation and metabolism. Molecular systems biology, 3(1), 101."}
+
+[Term]
+id: KISAO_0000598
+name: hybrid Gibson - Milstein method
+is_a: KISAO_0000352 ! hybrid method
+property_value: definition "A hybrid stochastic method partitions the system into subsets of fast and slow reactions and approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the Gibson algorithm. Fixed time step Milstein is used for approximate numerical solution of CLE." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: http://purl.org/dc/terms/creator "MLB" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: seeAlso "http://identifiers.org/doi/10.1186/1471-2105-7-93" xsd:anyURI {comment="H.Salis, V. Sotiropoulos and Y. Kaznessis,'Multiscale Hy3S: Hybrid stochastic simulation for supercomputers', BMC Bioinformatics 7:93 (2006)."}
+
+[Term]
+id: KISAO_0000599
+name: hybrid Gibson - Euler-Maruyama method
+is_a: KISAO_0000352 ! hybrid method
+property_value: definition "A hybrid stochastic method partitions the system into subsets of fast and slow reactions and approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the Gibson algorithm. Fixed time step Milstein is used for approximate numerical solution of CLE." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: http://purl.org/dc/terms/creator "MLB" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: seeAlso "http://identifiers.org/doi/10.1186/1471-2105-7-93" xsd:anyURI {comment="H.Salis, V. Sotiropoulos and Y. Kaznessis,'Multiscale Hy3S: Hybrid stochastic simulation for supercomputers', BMC Bioinformatics 7:93 (2006)."}
+
+[Term]
+id: KISAO_0000600
+name: hybrid adaptive Gibson - Milstein method
+is_a: KISAO_0000352 ! hybrid method
+property_value: definition "A hybrid stochastic method partitions the system into subsets of fast and slow reactions and approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the Gibson algorithm. Fixed time step Milstein is used for approximate numerical solution of CLE." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: http://purl.org/dc/terms/creator "MLB" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+property_value: seeAlso "http://identifiers.org/doi/10.1186/1471-2105-7-93" xsd:anyURI {comment="H.Salis, V. Sotiropoulos and Y. Kaznessis,'Multiscale Hy3S: Hybrid stochastic simulation for supercomputers', BMC Bioinformatics 7:93 (2006)."}
+
+[Term]
+id: KISAO_0000606
+name: hierarchical stochastic simulation algorithm
+is_a: KISAO_0000241 ! Gillespie-like method
+relationship: KISAO_0000361 KISAO_0000029 ! Gillespie direct algorithm
+property_value: altLabel "hSSA" xsd:string {comment="EXACT"}
+property_value: definition "Fast, memory-efficient method for stochastic simulation of hierarchically organized models, such as a model of a cellular population where each cell in the population is represented by the same species and reactions." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: seeAlso "http://identifiers.org/doi/10.3389/fbioe.2014.00055" xsd:anyURI {comment="Watanabe, L. H., & Myers, C. J. (2014). Hierarchical stochastic simulation algorithm for SBML models of genetic circuits. Frontiers in bioengineering and biotechnology, 2, 55."}
+
+[Term]
+id: KISAO_0000607
+name: hierarchical Fehlberg method
+is_a: KISAO_0000086 ! Fehlberg method
+property_value: altLabel "hierarchical ODE integration method" xsd:string
+property_value: altLabel "hierarchical ordinary differential equation integration method" xsd:string
+property_value: altLabel "hODE" xsd:string {comment="EXACT"}
+property_value: definition "Method for continuous simulation of hierarchically organized models, such as a model of a cellular population where each cell in the population is represented by the same species and reactions." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: seeAlso "http://identifiers.org/doi/10.3389/fbioe.2014.00055" xsd:anyURI {comment="Watanabe, L. H., & Myers, C. J. (2014). Hierarchical stochastic simulation algorithm for SBML models of genetic circuits. Frontiers in bioengineering and biotechnology, 2, 55."}
+
+[Term]
+id: KISAO_0000608
+name: hierarchical flux balance analysis
+is_a: KISAO_0000437 ! flux balance analysis
+property_value: altLabel "hFBA" xsd:string {comment="EXACT"}
+property_value: altLabel "Hierarchical FBA" xsd:string {comment="EXACT"}
+property_value: altLabel "hierarchical FBA" xsd:string
+property_value: definition "Method for constraint-based simulation of hierarchically organized models, such as a model of a cellular population where each cell in the population is represented by the same species and reactions." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: seeAlso "http://identifiers.org/doi/10.3389/fbioe.2014.00055" xsd:anyURI {comment="Watanabe, L. H., & Myers, C. J. (2014). Hierarchical stochastic simulation algorithm for SBML models of genetic circuits. Frontiers in bioengineering and biotechnology, 2, 55."}
+
+[Term]
+id: KISAO_0000609
+name: embedded Runge-Kutta Prince-Dormand (8,9) method
+is_a: KISAO_0000302 ! embedded Runge-Kutta method
+property_value: altLabel "RK8PD" xsd:string {comment="EXACT"}
+property_value: definition "An embedded Runge-Kutta integrator of order 8(9)." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+
+[Term]
+id: KISAO_0000610
+name: composite-rejection stochastic simulation algorithm
+is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
+property_value: altLabel "SSA-CR" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: seeAlso "http://identifiers.org/doi/10.1063/1.2919546" xsd:anyURI {comment="Slepoy, A., Thompson, A. P., & Plimpton, S. J. (2008). A constant-time kinetic Monte Carlo algorithm for simulation of large biochemical reaction networks. The journal of chemical physics, 128(20), 05B618."}
+
+[Term]
+id: KISAO_0000611
+name: incremental stochastic simulation algorithm
+is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
+property_value: altLabel "iSSA" xsd:string {comment="EXACT"}
+property_value: definition "Performs local averaging over small time-intervals to compute statistics on typical behavior." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "https://identifers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+property_value: seeAlso "http://identifiers.org/doi/10.1109/ISCAS.2010.5537539" xsd:anyURI {comment="Winstead, C., Madsen, C., & Myers, C. (2010, May). iSSA: An incremental stochastic simulation algorithm for genetic circuits. In Proceedings of 2010 IEEE International Symposium on Circuits and Systems (pp. 553-556). IEEE."}
+
+[Term]
+id: KISAO_0000612
+name: implicit 4th order Runge-Kutta method at Gaussian points
+is_a: KISAO_0000064 ! Runge-Kutta based method
+property_value: altLabel "RK4IMP" xsd:string {comment="EXACT"}
+property_value: http://purl.org/dc/terms/created "2021-01-25" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:string {comment="iBioSim"}
+
+[Term]
+id: KISAO_0000613
+name: stochastic simulation algorithm with normally-distributed next reaction times
+is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
+property_value: altLabel "NMC" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+
+[Term]
+id: KISAO_0000615
+name: fully-implicit regular grid finite volume method with a variable time step
+is_a: KISAO_0000285 ! finite volume method
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+
+[Term]
+id: KISAO_0000616
+name: semi-implicit regular grid finite volume method with a fixed time step
+is_a: KISAO_0000285 ! finite volume method
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+
+[Term]
+id: KISAO_0000617
+name: IDA-CVODE hybrid method
+is_a: KISAO_0000352 ! hybrid method
+property_value: definition "Meta algorithm which chooses between IDA and CVODE depending on the problem to be solved.\n\nCVODE is used for ordinary differential equation (ODE) systems. IDA is used for differential-algebraic equation (DAE) systems." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/vcell" xsd:anyURI {comment="VCell"}
+
+[Term]
+id: KISAO_0000618
+name: bunker
+is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
+property_value: definition "A variant of the stochastic simulation algorithm (SSA) in which the time to the next reaction is equated to the mean inter-event time (inverse of the sum of the propensitites of the reactions) rather than sampled from a distribution parameterized by this mean inter-event time. In this method, the next reaction time is deterministic rather than stochastic as in SSA." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+
+[Term]
+id: KISAO_0000619
+name: emc-sim
+is_a: KISAO_0000335 ! generalized stochastic simulation algorithm
+property_value: definition "A variant of the stochastic simulation algorithm (SSA) in which the time to the next reaction is a constant equal to 1 time unit. In this method, the next reaction time is deterministic rather than stochastic as in SSA." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/ibiosim" xsd:anyURI {comment="iBioSim"}
+
+[Term]
+id: KISAO_0000620
+name: parsimonius flux balance analysis
+is_a: KISAO_0000437 ! flux balance analysis
+property_value: altLabel "pFBA" xsd:string
+property_value: definition "A technique for selecting a flux distribution which is parsimonious by some metric, such as a solution which has the minimal number of active fluxes or a solution which has the smallest sum of active fluxes." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000621
+name: stochastic simulation leaping method
+is_a: KISAO_0000333 ! accelerated stochastic simulation algorithm
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000622
+name: flux balance method
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000624
+name: method for solving a system of linear equations
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: definition "method for solving a system of linear equations\n\nExample system of equations:\n\n3x + 2y - z = 0\n2x - 2y + 4z = 0\n-x + 1/2y - z = 0" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000625
+name: dense direct solver
+is_a: KISAO_0000624 ! method for solving a system of linear equations
+property_value: altLabel "denese" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "CVODE" xsd:string
+
+[Term]
+id: KISAO_0000626
+name: band direct solver
+is_a: KISAO_0000624 ! method for solving a system of linear equations
+property_value: altLabel "banded" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "CVODE" xsd:string
+
+[Term]
+id: KISAO_0000627
+name: diagonal approximate Jacobian solver
+is_a: KISAO_0000624 ! method for solving a system of linear equations
+property_value: altLabel "diagonal" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "CVODE" xsd:string
+
+[Term]
+id: KISAO_0000630
+name: root-finding method
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: definition "Method for finding the root of a function (f(x) = 0)." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000631
+name: iterative root-finding method
+is_a: KISAO_0000630 ! root-finding method
+property_value: definition "Iterative method for finding the root of a function (f(x) = 0)." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000632
+name: functional iteration root-finding method
+is_a: KISAO_0000631 ! iterative root-finding method
+property_value: definition "Iterative method for finding the root of a function f(x) given by\n\ny^{n(m+1)} = h_{n} β_{n,0} f(t_{n}, y^{n(m)}) + a_n\n\nThis method only involves evaluations of f. This method is suitable for non-stiff functions." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "CVODE" xsd:string
+property_value: seeAlso "https://bookdown.org/rdpeng/advstatcomp/functional-iteration.html" xsd:anyURI {comment="Roger Peng. Advanced Statistical Computing."}
+
+[Term]
+id: KISAO_0000657
+name: sequential logical simulation method
+is_a: KISAO_0000448 ! logical model simulation method
+property_value: definition "Qualitative (logical) models specify the evolution rules of their components. In the case of a sequential updating, nodes are updated sequentially in a pre-determined deterministic order." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+
+[Term]
+id: KISAO_0000658
+name: logical model analysis method
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: definition "A method for analyzing a logical model, such as finding its fixed points." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000659
+name: Naldi MDD logical model stable state search method
+is_a: KISAO_0000660 ! logical model stable state search method
+property_value: altLabel "Naldi Multi-valued Decision Diagram stable state search method" xsd:string
+property_value: definition "Efficient method for determining the stable states of a regulatory graph using a Multi-valued Decision Diagram (MDD) representation of the logical functions." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: seeAlso "http://identifiers.org/doi:10.1007/978-3-540-75140-3_16" xsd:anyURI {comment="Aurélien Naldi, Denis Thieffry and Claudine Chaouiya. Decision Diagrams for the Representation and Analysis of Logical Models of Genetic Networks. Computational Methods in Systems Biology 2007, 4695."}
+
+[Term]
+id: KISAO_0000660
+name: logical model stable state search method
+is_a: KISAO_0000658 ! logical model analysis method
+property_value: definition "Method for determining the stable states of a regulatory graph." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000661
+name: logical model trap space identification method
+is_a: KISAO_0000658 ! logical model analysis method
+property_value: definition "Method for determining the trap spaces, or stable motifs or symbolic stable states, of a regulatory graph," xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isOrganizational "true" xsd:boolean
+
+[Term]
+id: KISAO_0000662
+name: Klarner ASP logical model trap space identification method
+is_a: KISAO_0000661 ! logical model trap space identification method
+property_value: altLabel "Klarner Answer Set Programming logical model trap space identification method" xsd:string
+property_value: definition "Optimization-based method rooted in answer set programming (ASP) for computing the trap spaces of a regulatory graph." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: seeAlso "http://identifiers.org/doi:10.1007/s11047-015-9520-7" xsd:anyURI {comment="Hannes Klarner, Alexander Bockmayr, and Heike Siebert. Computing maximal and minimal trap spaces of Boolean networks. Natural Computing 14.4 (2015): 535-544."}
+
+[Term]
+id: KISAO_0000663
+name: BDD logical model trap space identification method
+is_a: KISAO_0000661 ! logical model trap space identification method
+property_value: altLabel "Binary Decision Diagram logical model trap space identification method" xsd:string
+property_value: definition "Method for determining the trap spaces of a regulatory graph using a Binary Decision Diagram (BDD)." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+
+[Term]
+id: KISAO_0000664
+name: Second order backward implicit product Euler scheme
+is_a: KISAO_0000000 ! modelling and simulation algorithm
+property_value: defaultLanguage "Method for solving Volterra equations. Uses the trapezoidal rule." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/xpp" xsd:anyURI {comment="XPP"}
+property_value: seeAlso "http://identifiers.org/doi:10.1093/comjnl/12.4.393" xsd:anyURI {comment="Peter Linz. Numerical methods for Volterra integral equations of the first kind. Computer Journal 12 (4): 393–397 (1969)."}
+property_value: seeAlso "https://doi.org/10.1137/1.9781611970852" xsd:anyURI {comment="Peter Linz. Analytical and Numerical Methods for Volterra Equations. 1985."}
+
+[Term]
+id: KISAO_0000668
+name: Numerical Recipes in C \"stiff\" Rosenbrock method
+is_a: KISAO_0000033 ! Rosenbrock method
+property_value: altLabel "stiff" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/xpp" xsd:anyURI {comment="XPP"}
+property_value: seeAlso "https://dl.acm.org/doi/10.5555/148286" xsd:anyURI {comment="William H. Press, Saul A. Teukolsky, William T. Vetterling & Brian P. Flannery. Numerical Recipes in C. The Art of Scientific Computing, 2nd Edition, 1992. Chapter 16. Pages 739-741."}
+property_value: seeAlso "Implementation of the Kaps and Rentrop using the parameters recommended by Shampine and Watts." xsd:string
+property_value: seeAlso "Shampine, L.F., and Watts, H.A. 1977, in Mathematical Software III, J.R. Rice, ed. (New York: Academic Press), pp. 257–275; 1979, Applied Mathematics and Computation, vol. 5, pp. 93–121." xsd:string
+
+[Term]
+id: KISAO_0000669
+name: Resource Balance Analysis
+is_a: KISAO_0000407 ! steady state method
+property_value: altLabel "RBA" xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/rbapy" xsd:anyURI {comment="RBApy"}
+property_value: seeAlso "https://doi.org/10.1016/j.automatica.2011.02.038" xsd:anyURI {comment="A. Goelzer, V. Fromion, G. Scorletti. Cell design in bacteria as a convex optimization problem. Automatica, 47(6):1210-1218 (2011)."}
+
+[Term]
+id: KISAO_0000672
+name: Numerical Recipes in C \"quality-controlled Runge-Kutta\" method
+is_a: KISAO_0000321 ! Cash-Karp method
+property_value: altLabel "rkqs" xsd:string
+property_value: definition "Cash-Karp method with step size adjustment." xsd:string
+property_value: http://purl.org/dc/terms/creator "JRK" xsd:string
+property_value: isImplementedIn "http://identifiers.org/biosimulators/xpp" xsd:anyURI {comment="XPP"}
+property_value: seeAlso "https://dl.acm.org/doi/10.5555/148286" xsd:anyURI {comment="William H. Press, Saul A. Teukolsky, William T. Vetterling & Brian P. Flannery. Numerical Recipes in C. The Art of Scientific Computing, 2nd Edition, 1992. Chapter 16. Pages 719."}
+
+[Typedef]
+id: KISAO_0000245
+name: has characteristic
+property_value: definition "'has characteristic' links algorithms to the characteristics, they possess." xsd:string
+domain: KISAO_0000000 ! modelling and simulation algorithm
+disjoint_from: KISAO_0000360 ! uses
+inverse_of: KISAO_0000268 ! is characteristic of
+
+[Typedef]
+id: KISAO_0000246
+name: is hybrid of
+property_value: definition "The basic idea of hybrid simulation methods is to combine the advantages of complementary simulation approaches: the whole system is subdivided into appropriate parts and different simulation methods operate on these parts at the same time.\n'is hybrid of' is a relation between the complex simulation method and algorithms it applies to the different parts of the system." xsd:string
+property_value: seeAlso "http://identifiers.org/doi/10.1093/bib/bbn050" xsd:anyURI {comment="Biochemical simulations: stochastic, approximate stochastic and hybrid approaches. Pahle J. Brief Bioinform. 2009 Jan;10(1):53-64. Epub 2009 Jan 16."}
+range: KISAO_0000000 ! modelling and simulation algorithm
+is_a: KISAO_0000360 ! uses
+
+[Typedef]
+id: KISAO_0000250
+name: is parameter of
+property_value: definition "'is parameter of' is an inverse of 'has parameter' and links parameters to the algorithms which use them." xsd:string
+range: KISAO_0000000 ! modelling and simulation algorithm
+inverse_of: KISAO_0000259 ! has parameter
+
+[Typedef]
+id: KISAO_0000259
+name: has parameter
+property_value: definition "'has parameter' links algorithms to the parameters they use." xsd:string
+domain: KISAO_0000000 ! modelling and simulation algorithm
+
+[Typedef]
+id: KISAO_0000268
+name: is characteristic of
+property_value: definition "'is characteristic of' is an inverse of 'has characteristic' and links characteristics to the algorithms which possess them." xsd:string
+range: KISAO_0000000 ! modelling and simulation algorithm
+
+[Typedef]
+id: KISAO_0000359
+name: is similar to
+property_value: definition "A relationship indicating that two entities are similar to each other." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+is_reflexive: true
+is_symmetric: true
+
+[Typedef]
+id: KISAO_0000360
+name: uses
+property_value: definition "A relation between algorithms indicating that one algorithm uses another one (for example, if the algorithm switches between several algorithms)." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+domain: KISAO_0000000 ! modelling and simulation algorithm
+range: KISAO_0000000 ! modelling and simulation algorithm
+inverse_of: KISAO_0000399 ! is used by
+
+[Typedef]
+id: KISAO_0000361
+name: is generalization of
+property_value: definition "A relation between kinetic simulation algorithms, indicating that one is a generalization of another (e.g.if one extends another to suit systems with more general characteristics )." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+domain: KISAO_0000000 ! modelling and simulation algorithm
+range: KISAO_0000000 ! modelling and simulation algorithm
+is_a: KISAO_0000359 ! is similar to
+
+[Typedef]
+id: KISAO_0000399
+name: is used by
+property_value: definition "A relation between algorithms indicating that one algorithm is used by another one (for example, if the algorithm switches between several algorithms). 'is used by' is inverse of 'uses'." xsd:string
+property_value: http://purl.org/dc/terms/creator "AZ" xsd:string
+

From be639af47ca294ba4d570b9a18c569bf2a72dab5 Mon Sep 17 00:00:00 2001
From: Logan Drescher <drescher@uchc.edu>
Date: Wed, 27 Nov 2024 15:15:07 -0500
Subject: [PATCH 2/2] Swapped assert for RuntimeException

---
 vcell-core/src/main/java/cbit/util/kisao/KisaoTermParser.java | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/vcell-core/src/main/java/cbit/util/kisao/KisaoTermParser.java b/vcell-core/src/main/java/cbit/util/kisao/KisaoTermParser.java
index 2b9fe617da..1a5efdddfe 100644
--- a/vcell-core/src/main/java/cbit/util/kisao/KisaoTermParser.java
+++ b/vcell-core/src/main/java/cbit/util/kisao/KisaoTermParser.java
@@ -29,7 +29,7 @@ KisaoOntology parse() {
 		boolean inState = false;
 
 		InputStream is = KisaoTermParser.class.getClassLoader().getResourceAsStream(Kisao_OBO);
-        assert is != null;
+		if (is == null) throw new RuntimeException("Unable to load OBO file necessary for KiSAO!");
 
 		try {
 			for (String line : (new BufferedReader(new InputStreamReader(is))).lines().toList()){