Alignement Multiple de Données Génomiques et Post-Génomiques : Approches Algorithmiques

Yves-Pol Denielou 1
1 BAMBOO - An algorithmic view on genomes, cells, and environments
Inria Grenoble - Rhône-Alpes, LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558
Abstract : Multiple alignment of biological networks is used to extract functional information from high-throughput data represented by graphs. This data can be protein-protein interactions, metabolic pathways or even the gene layout on a chromosome. We start by giving a precise formalism, based on the notions of layered datagraph and alignment multigraph (MGA), which defines local multiple alignments in the datagraph, allowing for example the tuning of the topology conservation between networks. Next, we present a new algorithm that builds and partitions the MGA ''on the fly", which allows us to deal with alignment of numerous biological networks. In a second part, we extend the formalism to be able to recover alignments - which we call ''partial" - when there are missing nodes on some networks. We explain the algorithms we have designed to compute those alignments, and then we give some improvements and some variants tailored to deal with specific biological problems.
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Yves-Pol Denielou. Alignement Multiple de Données Génomiques et Post-Génomiques : Approches Algorithmiques. Autre [cs.OH]. Université de Grenoble, 2010. Français. ⟨tel-00610419⟩

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