Computational Biology of Infection Research

The research of the group focuses on the data-driven analysis of biological questions from infection research, as well as method development to solve prediction problems for large biological data sets.


Our Research

To address problems of either medical or biotechnological relevance we are using pattern recognition techniques and phylodynamic methods. An example  is the development of phylodynamic techniques, which combine phylogenetic and epidemiological information to infer different aspects of the evolutionary dynamics of rapidly evolving populations. We apply these techniques to analyze genomic data of microbial communities (also known as metagenomic data), of influenza viruses and of cancer cells.

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