Research
What we do
At the interface of biology and computer science, we seek to better understand evolutionary and functional relationships between genes, genomes, and species. We are particularly interested in comparing gene repertoires across the Tree of Life, and investigating their role in the emergence of molecular functions and phenotypic traits.
Key underlying questions are:
- How can we extrapolate current biological knowledge, concentrated in a few model organisms, to the rest of life?
- Conversely, how can we exploit the wealth and diversity of life to better grasp key evolutionary innovations that shaped an organism of interest?
- How to devise methods that get more accurate with more data?
To tackle these questions, we work on interrelated aspects of comparative genomics, from the initial genome sequence assessment, to homology inference, to the downstream analyses. Our main goals are:
Large-scale homology and orthology inference
- Compare a large diversity of genomes across the Tree of Life
- Deal with the exponential increase of draft genome sequences by creating scalable methods
Assessment genome quality
- Use information on the evolutionary conservation of genes to evaluate protein-coding gene annotations
Fundamental and applied biological applications
- Infer gene function using comparative phylogenetic methods
- Zero in on evolutionary innovations in specific clades and their link to adaptive phenotypes
- Collaborate with industry to transfer knowledge from model organisms and find relevant candidate genes for agricultural and pharmaceutical purposes
Our activities are divided between bioinformatics methods and resource development, and their application – typically involving collaborations with experimentalists to answer interesting biological questions. With the help of talented people on the team, the different projects fit together to make up what we call the “OMA Ecosystem,” i.e. the collection of tools, software, data downloads, interactive visualizations and other resources, which are associated with the OMA knowledgebase.
