Christophe Dessimoz
Computational Evolutionary Biology and
Genomics Group
University of Lausanne
Group Webpage
Twitter button
Twitter button

What do we do?

At the interface of biology and computer science, we seek to better understand evolutionary and functional relationships between genes, genomes and species. Key underlying questions are: 1) How can we extrapolate current biological knowledge, concentrated in a few model organisms, to the rest of life? 2) Conversely, how can we exploit the wealth and diversity of life to better grasp an organism of interest? 3) Can we summarize the evolutionary history of species as a sparse mixture of tree topologies? Our activities are divided between bioinformatics methods and resource development, and their application – typically with experimentalists.

Highlights 2017

This was a big year for the OMA project. We introduced changes to the algorithm to make it more robust for duplicated genes evolving at different rates, and to make it more scalable. We also released numerous improvements for our end users in the form of better web and programmatic interfaces. We completed a collaborative study of structural variation within the known world population of fission yeast (Jeffares et al, Nat Comm). We observed a surprisingly rapid turnover of duplications within the population, and strong association with phenotypic traits. More information can be found in this blog post.

Publications 2017

  • Train et al. Orthologous matrix (OMA) algorithm 2.0: more robust to asymmetric evolutionary rates and more scalable hierarchical orthologous group inference, Bioinformatics, 2017, i1-i8 (ISMB 2017 proceedings)
  • Jeffares et al. Transient structural variations have strong effects on quantitative traits and reproductive isolation in fission yeast. Nat Commun. 2017, 8:14061
  • Dessimoz C and Škunca N. The Gene Ontology Handbook. Methods in Molecular Biology, 2017, Springer (New York), Vol. 1446

Our main research topic: