Algorithmic Bioinformatics

The research group Algorithmic Bioinformatics develops data-driven mathematical models and new algorithmic methods to better understand biological processes. The work is highly interdisciplinary and is characterized by cooperations with both experimental partners and colleagues within computer science. We currently focus on the following topics:

  • Algorithms for Network Biology
  • Algorithmic Genomics 
  • Molecular graph models for biomolecular simulations

On the practical side, our focus is on dealing with large data sets and on developing automated and robust analysis pipelines.   



DFG funding for full resolution computational genomics

Mapping genomic variants is an important and necessary step for biomedical and fundamental research. Differences in our genomic sequences result in phenotypic differences that determine how, for example, the cells of a healthy and a diseased person differ from each other. In population genetics, genomic variants help to trace down our evolutionary histories.

Genomic differences are now routinely measured using high-throughput sequencing techniques. However, using standard techniques, we only...

Anton Betz Foundation supports cancer genomics computing at HHU

Developing mathematical models for cancer genomics is a focus area of the research group. Currently, we work together with researchers from Princeton and Microsoft Research to identify signaling pathways and mechanisms responsible for sensitivity or resistance of cancer cell lines that have been treated with anticancer drugs. Our mathematical models look for specific mutation patterns in big genomic data of large drug screening sequencing projects. In particular, we are interested in finding...

Office Address

Group Algorithmic Bioinformatics
Building 25.12 Level/Room 01.46
Universitätsstraße 1
40225 Düsseldorf

Section head

Prof. Dr. Gunnar W. Klau

Building: 25.12
Floor/Room: 01.46
Phone +49 211 81-10427
Fax +49 211 81-13464


Angela Rennwanz

Building: 25.12
Floor/Room: 01.44
Phone +49 211 81-10591
Fax +49 211 81-13464
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