Laboratory of Bioinformatics Analyses for Genomics and Metabolism
The aim of this PhD thesis is to achieve new methodological developments for the comparative study of pangenomes. This will involve the development of new bioinformatic methods for inter-pangenome comparisons, which will be particularly based on the developments carried out
The aim of this PhD thesis is to carry out methodological developments for the comparative study of pangenomes. Those developments will allow to explore the variable pangenome’s dynamic within and between bacterial clades. Firstly, a tool for detecting variable regions
Introduced in microbiology in 2005 by Medini et al. and Tettelin et al., pangenome approaches aim to compile the entire genomic diversity of a species. In these studies, we generally distinguish within the pangenome, the core genome: the set of
One consequence of increasing sequencing capacity is the the accumulation of \textit{in silico} predictions in biological sequence databanks. This amount of data exceeds human curation capacity and, despite methodological progress, numerous errors on the prediction of protein functions are made.
E. coli is the first causative agent among community-acquired bacteraemia and it is also the most abundant species among facultative anaerobic bacteria in human gastro-intestinal tract (Tenaillon et al., Nat. Rev. Microbiol, 2010; Martin et al., N. Engl. J. Med.,
The proportion of protein sequences of unknown function in public databases stills very important (42% of UniProt sequences are labelled as “hypothetical”, “uncharacterized”, “unknown” or “putative”). On the other hand, a number of enzyme activities (about 30%) remain orphan (i.e.
Prokaryotes —bacteria and archaea— are diverse, ubiquitous organisms with vast impacts on health, soil, and ocean ecosystems. Large-scale genome sequencing and pangenomics have revealed their molecular diversity, especially the role of Mobile Genetic Elements (MGEs). Pangenomics analyzes genetic variability across
Localisé au CEA/Genoscope, un centre de recherche scientifique dédié à la génomique environnementale, le Laboratoire d’Analyses Bioinformatiques pour la Génomique et le Métabolisme (LABGeM, UMR8030, labgem.genoscope.cns.fr) s’intéresse à l’analyse et à l’exploration de la diversité des microorganismes et de leur