MAB: Méthodes et algorithmes pour la bio informatique

At the crossroad between biology and computer science, bioinformatics aims at solving biological problems using computational approaches. These techniques cover a broad range of areas, from theoretical biology to agronomy through health and environmental science. The main objective of our team is to provide new methods (string and tree algorithms, optimization methods, combinatorial approaches and  statistical learning methods) to answer important biological questions (evolution, phylogenetics, comparative genomics, functional annotation of genes and proteins, malaria, HIV, cancer).

Research themes are organized in three main axes : Treatment of sequencing data, Methods for evolution analysis, and Tools for functional annotation. The software developed by the team are available on the ATGC platform.



No permanents


April 2018 - Renewing Felsenstein's phylogenetic bootstrap in the era of big data has been published in Nature.

October 2018 - The CNRS annual activity report highlights software SAVAGE :


Optimisation, Classification, Transcriptomes, Cancer, Algorithmic of text and trees, Combinatoric, Probabilistic and statistic modeling, Phylogeny, Hight speed sequencing, Genomes, HIV, Proteomes, Malaria

Last update on 22/10/2018