Bioinformatics, cancer data science, computational biology, tumor evolution
What we investigate
Our research in computational biology, bioinformatics, and biostatistics is at the interface of mathematics, statistics, and computer science with biology and medicine. It includes statistical, evolutionary, and network modeling of molecular and clinical data to support the rational design of medical interventions.
Our research in more detail
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.
SKINTEGRITY.CH Principal Investigators are underlined:
- Singer J, Kuipers J, Jahn K, and Beerenwinkel N (2018). Single-cell mutation identification via phylogenetic inference. Nat Commun, 9: 5144.
- Dimitrakopoulos C, Hindupur SK, Hӓfliger L, Behr J, Montazeri H, Hall MH, and Beerenwinkel N (2018). Network-based integration of multi-omics data for prioritizing cancer genes. Bioinformatics 34: 2441-2448.
- Singer J, Irmisch A, Ruscheweyh H-J, Singer F, Toussaint NC, Levesque MP, Stekhoven DJ, and Beerenwinkel N (2019). Bioinformatics for Precision Oncology. Briefings in Bioinformatics, 20: 778-788.
- Noble R, Burri D, Kather JN, and Beerenwinkel N (2020). Spatial structure governs the mode of tumour evolution. https://doi.org/10.1101/586735.