Research mission
Our group implements the systems biology approach: mechanistic modeling of known and predicted interactions between molecules and/or biological entities (metabolites, enzymes, genes, RNA, drugs, membranes, cells). Integrating omics data into mechanistic mathematical models enables extracting more knowledge from experimental data.    
Group's Homepage: https://www.biosystems.lv/

Team members:

Dr.sc.ing Egils Stalidzans

PhD Ehsan Motamedian

M.sc. Janis Kurlovics

M.sc.Liva Kristiana Lukasa

Focus areas  

-    different types of mathematical modeling to target different cancer types, antimicrobial resistance, pharmacokinetics, etc.
-    genome-scale modeling and optimization of metabolism, including integration of omics data: personalized models at sample level enable analysis of differences in metabolism between samples.
-    ordinary differential equation (ODE) based modeling of metabolic, signaling, transport and other processes.
-    software development for specific tasks    

Key discoveries

-    first physiology-based pharmacokinetic model for metformin in humans based on pre-clinical data,
-    determination of passive metformin transport rate through cellular membrane,
-    software development, including contribution to COBRA v3.0 and COPASI software
-    definition of sustainable metabolic engineering (SME) approach enabling sustainable strain design for biotechnological needs
      
Methodology

-    genome-scale metabolic modeling relies on steady state assumption of cellular processes and mass conservation law: any atom or charged particle as part of molecules have to come out from the cell. Thanks to enzymes atoms change their neighbors, becoming part of other molecules: all that is accounted for by the list of reactions that are executed by enzymes that are encoded by genes.
-    ODE-based models allow to gain insight into how different processes behave in time. Models can be used also for the estimation of process parameters by fitting the model behavior to the experimental data. Stochastic elements can be included.