Computational Biology

We develop computational methods for assisting with biomedical decision processes by combining biological networks with multiple OMICS data types for unraveling the molecular basis of different diseases, for biomarker discovery, and for personalized medicine. In addition we study the evolution of genomes and gene regulatory networks, as well as genetic factors for bacterial "life styles", such as pathogenicity & virulence. Computationally, we focus on exact and heuristic methods for combinatorial optimization problems and machine learning approaches for OMICS data.