What we do

In the Computational Biochemistry Research Group, we are interested in the modelling and analysis of biological problems at the molecular level. In particular, our expertise lies in searching algorithms, optimizing algorithms, mathematical modelling, and computational systems. Most of our research efforts are concentrated on the Orthologous MAtrix (OMA) project. This particular project aims to produce, automatically, reliable orthologous groups of proteins that are derived from entire genomes.

Highlights 2017

The OMA Browser is a SIB-funded, publicly available resource that provides orthology predictions among publicly available proteomes from all domains of life. The most recent release of the OMA Browser covers now 2,103 complete genomes. The predictions are accessible through browsable and programmatic APIs. The underlying OMA algorithm is available as a standalone program to analyse custom genome datasets. The group is actively participating in several community benchmarking efforts focused on orthology and protein function prediction.

Find out more about the Group’s activities

Main publications 2017

  • Train CM et al. Orthologous Matrix (OMA) algorithm 2.0: more robust to asymmetric evolutionary rates and more scalable hierarchical orthologous group inference. Bioinformatics. 2017; 33:14, i75-i82
  • Altenhoff AM et al. The OMA orthology database in 2018: retrieving evolutionary relationships among all domains of life through richer web and programmatic interfaces. Nucleic acids res. 2017; 46 (D1), D477-D485
  • Forslund K et al. Gearing up to handle the mosaic nature of life in the quest for orthologs. Bioinformatics. 2017; 34:2, 323-329


eth zurich

Gaston Gonnet
Computational Biochemistry Research Group
ETH Zurich
Group Webpage


Domains of activity:

  • Evolution and phylogeny
  • Comparative genomics
  • Evolutionary biology
  • Metagenomics
  • Phylogeny
  • Software engineering

Domains of application:

  • Agriculture
  • Basic research