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The Rīga Stradiņš University (RSU) Bioinformatics Group specialises in analysing and integrating genomic, transcriptomic, microbiome, and other omics data with clinical or phenotype information to support precision medicine.

The group employs different data integration methods, including quantitative trait loci (QTL) mapping, network-based approaches, and machine learning (ML) to identify relationships between different data types, linking them to clinical or phenotypic outcomes. The group's current activities focus on research software quality and automated computational workflows, emphasising FAIR (Findable, Accessible, Interoperable, and Reusable) principles.

Recently, the Bioinformatics Group expanded to include a Computational Systems Biology team led by Dr. sc. ing. Egils Stalidzāns. This team investigates complex biological mechanisms by constructing mathematical models that replicate system behaviour-based on interactions between system elements. Their work primarily involves modelling genome-wide metabolic processes (integrating diverse omics data) and physiology-based pharmacokinetic processes, furthering the precision medicine approach.

For more details on this team's work, visit the Computational Systems Biology group's website.