Computational Genomics

The Medical Genomics group is developing computational methods for OMICs data analysis with a strong focus on NGS applications in clinical diagnostics and precision medicine. We develop novel algorithms for identification and prioritization of causal mutations in rare and familial diseases as well as in large-scale cancer studies.

As part of the International Cancer Genome Consortium (ICGC) the group develops methods for identification of cancer driver and risk genes, somatic copy number alterations as well as somatic indels. The identification of disease or cancer specific alterations at molecular level is a prerequisite for optimized individual treatment of patients. As complementary field of activity the group is developing techniques for genomic and metagenomic analysis of pathogenic and non-pathogenic bacteria that will provide a better understanding of pathogenicity, host defence, antibiotic resistance and the impact of drugs on the human microbiome.

Prof. Dr. Stephan Ossowski

Group Leader

Stephan Ossowski

has obtained a PhD in Computational Biology from the Max-Planck Institute Germany in 2010 for his work on the computational analysis of next generation sequencing (NGS) data, genome re-sequencing and population genetics. In 2008 he published the first whole-genome analysis of a plant genome using NGS technology and has since worked on developing novel computational and statistical methods for NGS analysis. After a short stay at the MIT in Boston he has started as group leader at the Centre for Genomic Regulation in Barcelona. His lab developed experimental and computational methods for medical genomics and epigenomics, with a strong focus on NGS applications in clinical diagnostics and precision medicine.

In 2017 Stephan Ossowski became Professor for Medical Genomics at the Institute for Medical Genetics and Applied Genomics at the University of Tübingen. He is currently interested in developing novel methods in the fields of rare disease and cancer diagnostics, tumor evolution, cancer susceptibility, liquid biopsy, antibiotic resistance detection and Nanopore sequencing.