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Recherche de similarités dans les séquences d'ADN : modèles et algorithmes pour la conception de graines efficaces

Laurent Noé 1
1 ADAGE - Applying discrete algorithms to genomics
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Most commonly used similarity search methods in genomic sequences are heuristic ones. These are based upon text filtering that allows one to infer potential regions of similarity.
This thesis proposes new filter definitions to search for similarities in genomic sequences, and fast algorithms to measure the efficiency of these filters.
More precisely, we study the spaced seed model and propose an algorithm to measure the seed efficiency on similarities of a certain kind, called homogeneous similarities. A generic algorithm has also been developed to measure the seed efficiency, together with an extension of the spaced seed model called subset seed. Finally, we propose and analyze a multi-seed approach in the framework of lossless filtration, and apply it to the problem of oligonucleotide design.
Several software tools have been developed to search for similarities as well as to design seed-based filters.
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Submitted on : Thursday, December 25, 2008 - 10:42:04 AM
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Laurent Noé. Recherche de similarités dans les séquences d'ADN : modèles et algorithmes pour la conception de graines efficaces. Autre [cs.OH]. Université Henri Poincaré - Nancy 1, 2005. Français. ⟨NNT : 2005NAN10118⟩. ⟨tel-01748141v3⟩

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