Benchmark-Models-PEtab

A collection of mathematical models with experimental data in the PEtab format as benchmark problems in order to evaluate new and existing methodologies for data-based modelling. The publication for the introduction and analysis of the benchmark problem collection is available at https://academic.oup.com/bioinformatics/article/35/17/3073/5280731.

Contributions to the collection are very welcome. For this, please create a new branch, add your model and test your files with the provided functions, and start a pull request. We will then check your model and merge it into the collection. We are continuously working on the extension of the collection.

Overview

Model ID	Conditions	Estimated Parameters	Events	Measurements	Observables	Species	References
Alkan_SciSignal2018	73	56	0	1733	12	36	[1]
Bachmann_MSB2011	36	113	0	541	20	25	[1]
Beer_MolBioSystems2014	19	72	0	27132	2	4	[1]
Bertozzi_PNAS2020	2	3	0	138	1	3	[1]
Blasi_CellSystems2016	1	9	0	252	15	16	[1]
Boehm_JProteomeRes2014	1	9	0	48	3	8	[1]
Borghans_BiophysChem1997	1	23	0	111	1	3	[1]
Brannmark_JBC2010	8	22	0	43	3	9	[1]
Bruno_JExpBot2016	6	13	0	77	5	7	[1]
Chen_MSB2009	4	155	0	120	3	500	[1]
Crauste_CellSystems2017	1	12	0	21	4	5	[1]
Elowitz_Nature2000	1	21	0	58	1	8	[1]
Fiedler_BMC2016	3	22	0	72	2	6	[1]
Fujita_SciSignal2010	6	19	0	144	3	9
Giordano_Nature2020	1	50	0	313	7	13	[1]
Isensee_JCB2018	123	46	0	687	3	25	[1]
Laske_PLOSComputBiol2019	3	13	0	42	13	41	[1] [2] [3]
Lucarelli_CellSystems2018	16	84	0	1755	65	33	[1]
Okuonghae_ChaosSolitonsFractals2020	1	16	0	92	2	9
Oliveira_NatCommun2021	1	12	0	120	2	9
Perelson_Science1996	1	3	0	16	1	4	[1]
Rahman_MBS2016	1	9	0	23	1	7
Raimundez_PCB2020	170	136	0	627	79	22
SalazarCavazos_MBoC2020	4	6	0	18	3	75
Schwen_PONE2014	19	30	0	286	4	11	[1]
Sneyd_PNAS2002	9	15	0	135	1	6	[1]
Weber_BMC2015	2	36	0	135	8	7	[1]
Zhao_QuantBiol2020	7	28	0	82	1	5	[1]
Zheng_PNAS2012	1	46	0	60	15	15	[1]

License

Any original content in this repository may be used under the terms of the BSD-3-Clause license. Different terms may apply to models and datasets, for which we refer the user to the original publications that are referenced in the respective SBML files.