Omics data provide a comprehensive amount of molecular profiles from biological samples (e.g. Genomics, Epigenomics, Transcriptomics, Proteomics, Metabolomics …). EHR or electronic health records are digital records of health information alongside personal information (age, ethnicity, gender, …).
As omics technologies become more widely used in the clinical environment, integrating omics data within EHRs will become increasingly important for interpretation and clinical decision support. However, it has been a challenge to both add the omics data into the EHRs, due to their size and complexity and provide easily interpretable results that could be used by clinicians.
Integrative multi-omic data analysis is of growing importance because it provides a holistic view of molecular fingerprints for each patient’s condition.
This project aims to provide an easily manageable database to store both patient’s EHRs and -omics data and provide clinicians with readable and easily interpretable output that helps them in the process of decision taking.
As a start, and due to time constraint, we will be focusing on integrating transcriptomic data first into our project.
- Incorporate more Omics data into our tool
- Ensure data interpretability and thereafter data integration.
- Use Artificial Intelligence to provide more in depth analysis with detailed output.
- Abdellah IDRISSI AZAMI, PhD candidate, [email protected], UM6SS, Casablanca, Morocco.
- Nihal HABIB, PhD candidate, [email protected], UM6SS, Casablanca, Morocco.
- Abdesselam BOUGDIRA, PhD in Engineering Sciences, [email protected],Laboratory of Engineering Sciences, USMBA, Fez, Morocco.
- Mustapha LEMSYAH, Engineering student, [email protected], High-Tech, Rabat, Morocco.
- Douae EL GHOUBALI, PhD candidate, [email protected], UM6SS, Casablanca, Morocco.