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About

I joined the Bioinformatics Hub in 2016 after a curriculum widely dedicated to Bioinformatics studies, and more precisely to Phylogeny and Evolution, topics of my PhD thesis.

At Institut Pasteur, I am involved in projects dealing with sequences homology: alignments, HMM profiles, making homologous family databases, kmers signatures. I am also a developer (Python / C++) with a solid interest in optimization as well as in developing usable tools for final user such as automated pipeline for metagenomics sequence analysis.

I’m currently embedded in the Laboratory of Pathogen Discovery lead by Marc Eloit (80% of my work time). My main task in this team is to develop strategies to identify, in their metagenomics samples, new pathogens, or new combination pathogen / symptoms. The rest of my time, I manage small projects and participate to the Hub life. I am currently experimenting with functional programming (for now, using Python) and its applicability to bioinformatics issues.

Courses

CV

Formation

Doctorat (2013)

Bio-informatique (Biologie de l’Évolution), sous la direction de Guy Perrière, LBBE, Université de Lyon. Recherche automatisée de motifs dans les arbres phylogénétiques.
Ce doctorat a été l’occasion de s’interroger sur la manière d’extraire efficacement l’information phylogénétique de collections d’arbres de familles de gènes homologues, en utilisant l’information topologique que ces arbres contiennent, de la même manière qu’on le fait en analysant un arbre visuellement. J’ai pour cela créé un formalisme qui permette de décrire ces motifs d’arbres ainsi qu’une suite logicielle pour exécuter ces requêtes sur des milliers d’arbres en quelques secondes. Cette suite logicielle a été publiée dans BMC Bioinformatics : Bigot et al. 2013 (10.1186/1471-2105-14-109).
Ce concept de recherche de motifs topologiques peut être utilisé pour décrire des motifs précis correspondant à une liste de contraintes, mais aussi d’une manière plus générique, d’extraire automatiquement les arbres ne contenant qu’une seule version de gène par espèces (arbres unicopies) ou encore de trouver la meilleure racine par rapport à un arbre d’espèces de référence, ou en utilisant les duplications contenues dans l’arbre de gènes.

Thèse de doctorat : https://tmgo.net/~thomas/these_doctorat

Master (2009)

Santé et Populations (spécialité Bioinformatique, Biostatistiques, Génome), Université Lyon 1.

Publications

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