Team members

Computational biology

The Computational Biology group addresses biological problems using computational methods, focusing on mitochondria as important metabolic organelles and on the evolution of biological systems.

Mitochondrial computational biology:  One of our research interests is to understand mitochondrial heterogeneity and diversity of structure, function and expression dynamics across different tissues, but also in different disease conditions. We use big data and big data integration techniques to learn how mitochondria adapt to their cellular environment. Our data visualization and integration platform mitoXplorer ( helps us use omics data to investigate this mitochondrial behaviour. 

Network biology: In a second project, we use complex networks to investigate the temporal behaviour of biological systems – monitored by temporal protein or RNA expression dynamics. With the help of these techniques, we can also unravel different phases of mitochondrial expression dynamics in development, ageing or in disease progression. 

Evolutionary computational biology:  We are also interested in evolutionary computational biology on sequence, cellular, and organismal level. We currently have several projects related to evolutionary computational biology. On sequence level, we are investigating the evolution of short linear motifs in proteins (SLiMs) and look specifically at predatory, as well as mechano-sensing motifs (in collaboration with the team of Tam Mignot). On a cellular level, we look at the evolution of epithelia in the most primitive metazoan organisms (sea-water sponges) as an important structure to define organismal and tissue boundaries (in collaboration with Andre le Bivic and Carole Borchiellini). On an organismal level, we look at the evolution of predatory traits in bacteria (in collaboration with the lab of Tam Mignot). 

Computational tool development for biological data mining and integration: Our lab is developing user-friendly tools for general data analysis, data mining and data integration for the research community. Find out here what these are and where to find them. 

Interactome view of the mitoXplorer web-server. Circles indicate mitochondrial processes, blue and red up- and down-regulated genes within them; lines indicate interactions between proteins.


Our last publications


of the team


They contributed to our research
Pierrelee Michael
Data Scientist, Capgemini Engineering, Strasbourg, France
Pfeiffer Friedhelm
Yeroslaviz Assa
Service Bioinformatician, MPI of Biochemistry, Martinsried, Germany
Yim Annie
Senior Data Science Consultant at Machine Learning Reply, Munich, Germany
Prytuliak Roman
Senior Consultant at d-fine, Munich, Germany
Sergej Nowoshilow
Principal Scientist at Boehringer Ingelheim, Vienna, Austria

Funding bodies

They support our research
Fondation Recherche Medicale