What do we do?
At the Evolutionary Bioinformatics Group we are mainly concerned with determining the role of evolutionary innovation and constraint in animals. For this, we develop methods and databases to extract reliable information from genome and transcriptome data. These databases include Bgee, a database for gene expression evolution, Selectome, a database of positive selection. In developing these resources, we also conduct research on ontologies, biocuration, and high-performance computing. Our biological focus is to link Evo-Devo with phylogenomics. We notably study the role of gene duplication in divergence between genes and between species.
We added a new gene page to our Bgee database of gene expression evolution. Thanks to a new algorithm ranking expression information of different types, from RNA-seq to in situ hybridization, we are able to present first the most relevant expression patterns for a gene, even when it is expressed in hundreds of conditions.
The group has participated in a new paper resulting from the master’s degree course “Sequence a genome”, a course during which master’s degree students sequence, assemble and annotate new bacterial genomes, for the first time using PacBio and RNA-seq. The paper is based directly on the students’ work during the class.
Main publications 2016
- Kryuchkova N., Robinson-Rechavi M., 2016. A benchmark of gene expression tissue-specificity metrics. Briefings in Bioinformatics online doi: 10.1093/bib/bbw008
- Davydov I.I., Robinson-Rechavi M., Salamin N., 2016. State aggregation for fast likelihood computations in molecular evolution. Bioinformatics in press doi: 10.1093/bioinformatics/btw632
- Kryuchkova N., Robinson-Rechavi M., 2016. Tissue-specificity of gene expression diverges slowly between orthologs, and rapidly between paralogs. PLOS Computational Biology in press