Research
Biology and biomedicine strive for an integral understanding of cells, organisms, and populations, in order to develop novel diagnostic and therapeutic measures. Research in the Computational Biology Group aims at supporting the rational design of medical interventions in complex and rapidly evolving biosystems. To achieve this goal, we develop models and algorithms for the statistical analysis of high-throughput molecular data, we reconstruct and analyze biological networks and predict the effect of perturbations, and we design evolutionary models of rapidly adapting disease-causing agents. We are engaged in several personalized medicine efforts, particularly in oncology and virology.
Selected review articles:
- external pageCancer Evolution: Mathematical Models and Computational Inferencecall_made
Beerenwinkel et al., Syst Biol, 2015
- external pageRecent advances in inferring viral diversity from high-throughput sequencing datacall_made
Posada-Cespedes et al., Virus Res, 2017 - external pageFrom hype to reality: data science enabling personalized medicinecall_made
Fröhlich et al., BMC Med, 2018