Prof. Dr. Niko Beerenwinkel
Area of Research
Description of Research Interest
We develop statistical models and computational methods for the analysis and design of biosystems. Our goal is to support the rational design of medical interventions based on large-scale molecular profiling data. To achieve this goal, we develop models and algorithms for the statistical analysis of high-throughput sequencing data, we 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. A recent major focus in both application domains is the analysis of single-cell data. In computational oncology, we develop methods for the reconstruction of the evolutionary history of tumors from single-cell sequencing data. In computational virology, we analyze single-cell transcriptomes of infected cells to understand viral latency and reactivation, and to optimize antiviral treatment. We also develop computational methods for the analysis of viral sequencing data from wastewater samples to enable disease montoring on a population scale.
Special Expertise
- Statistical modeling
- Evolutionary modeling
- ML/AI in Medicine
- Computational oncology
- Computational virology
Shareable Platforms, Services, Equipment & Infrastructure
- Cancer NGS data analysis pipeline (https://github.com/cbg-ethz/NGS-pipe)
- Viral NGS data analysis pipeline (https://cbg-ethz.github.io/V-pipe/)
- All software tools are available at https://github.com/cbg-ethz
Member of Collaborative/interdisciplinary Research Consortia
- Tumor Profiler Center (https://tumorprofilercenter.ch/)
- LOOP INTeRCePT (https://theloopzurich.ch/en/projekte/intercept/)
- Center for Pathogen Bioinformatics (https://www.sib.swiss/centre-for-pathogen-bioinformatics)
- WISE - Wastewater-based Infectious Disease Surveillance (https://wise.ethz.ch/)
