Olivier Gascuel

Méthodes et Algorithmes pour la Bioinformatique (MAB)
Institut de Biologie Computationnelle (IBC)
LIRMM-CNRS, 95 rue de la Galera,
34095 – Montpellier cédex - FRANCE
Tel. 33 (0) 4 67 41 85 47
Fax. 33 (0) 4 67 41 85 00
gascuel@lirmm.fr

Publications & Citations (Google Scholar)

Research interests

My main research interest is in the field of evolution and phylogeny. My focus is on the mathematical and computational tools and concepts, which form an essential basis of evolutionary studies (2005 book, 2007 book).

I am working on algorithms for phylogenetic inference. I authored BioNJ (Mol Biol Evol 1997) and, with Rick Desper, FastME (J Comp Biol 2002, Mol Biol Evol 2004). With Alexis Criscuolo we conceived the SDM distance-based method to combine gene trees into a species supertree (Syst Biol 2006), and the PhyD* algorithms to build trees from distance matrices with missing entries (BMC Bioinformatics 2008). With Mike Steel and Fabio Pardi, we worked on the theoretical foundations of distance-based tree inference (Mol Biol Evol 2006, Bull Math Biol 2010, PNAS 2012). With Stéphane Guindon we designed the PhyML software for maximum-likelihood tree inference (Syst Biol 2003, Highly Cited!). This software has been refined and enriched with several tools, most notably the aLRT branch supports (Syst Biol 2006, Syst Biol 2011). PhyML 3.0 paper (Syst Biol 2010) describes these novelties and extensive benchmarking with a number of DNA and protein data sets.

I am working on probabilistic models of sequence evolution, most notably proteins. With Quang Si Le we recently proposed several evolutionary models based on mixtures (Phil Trans Roy Soc B 2008, Mol Biol Evol 2012) or site partitions using available structural information (Syst Biol 2010). We also designed a new estimation method for amino acid replacement matrices and proposed the LG matrix (Mol Biol Evol 2008, Bioinformatics 2011). With Mike Steel we explored the impact of substitution models on the predictability of ancestral sequences (Math Biosciences 2010, ArXiv 2013).

During the last years, I turned part of my activities toward pathogens, most notably Plasmodium faciparum (main agent of malaria) and HIV. With P. falciparum, our aim was to decipher the function of its genes, most of them (60%) being fully unknown, while they could be potential targets for new drugs or vaccines. We used postgenomic data (mostly transcriptomes) and statistical learning approaches to propose functional predictions for a number of its genes (BMC Bioinformatics 2008, BMC Genomics 2010); these predictions are compiled in the PlasmoDraft database. We also refined the annotation of its proteins in structural domains (Bioinformatics 2009, BMC Bioinformatics 2012) and designed the RED2 method and program to search for regulation motifs (Genome Biology 2012). From an evolutionary perspective, we studied the origin of P. falciparum (BMC Evol Biol 2011) and implemented the PhyloType web server to extract relevant clusters or “phylotypes” from a phylogeny combined with extrinsic characters; PhyloType was applied to the phylogeography of HIV epidemics and other related questions (Bioinformatics 2013).