We utilize a diverse range of mathematical modeling techniques to analyze metabolism, cell signaling, and other biological processes. While Ordinary Differential Equation (ODE) models offer the most versatile framework, we also employ linear algebra-based genome-scale metabolic modeling and logical modeling for signaling pathways. Furthermore, our expertise extends to physiologically based pharmacokinetics (PBPK) and population pharmacokinetics (PopPK).
Tenured professor
Computational Systems Biology team, Rīga Stradiņš University
Project cooperation
Multi-omics integration in genome-scale metabolic models
Sample (biopsy) specific genome-scale metabolic model needs transcriptomics data. Proteomics and metabolomics make it more accurate.
Tenured professor at Computational Systems Biology team, Rīga Stradiņš University
Riga, Latvia
Project cooperation
In silico combinatorial therapy ranking
Genome-scale stoichiometric models of metabolism enable in silico ranking of metabolism-related drug synergy used in combinations.
Tenured professor at Computational Systems Biology team, Rīga Stradiņš University
Riga, Latvia
Project cooperation
Mechanistic mathematical modeling (systems biology approach)
Modelling molecular mechanisms reveals individual cellular component interactions, facilitating understanding of control mechanisms.
Tenured professor at Computational Systems Biology team, Rīga Stradiņš University
Riga, Latvia