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Communication dans un congrès

A Decomposition Approach for Discovering Discriminative Motifs in a Sequence Database

Abstract : This paper addresses the discovery of discriminative nary motifs in databases of labeled sequences. We consider databases made up of positive and negative sequences and define a motif as a set of patterns embedded in all positive sequences and subject to alignment constraints. We formulate constraints to eliminate redundant motifs and present a general constraint optimization framework to compute motifs that are exclusive to the positive sequences. We cast the discovery of closed and replication-free motifs in this framework and propose a two-stage approach whose last stage reduces to a minimum set covering problem. Experiments on protein sequence datasets demonstrate its efficiency.
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Communication dans un congrès
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https://hal.univ-angers.fr/hal-03256765
Contributeur : Okina Université d'Angers <>
Soumis le : jeudi 10 juin 2021 - 14:20:50
Dernière modification le : samedi 12 juin 2021 - 03:30:38

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2014lesaintecai.pdf
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David Lesaint, Deepak Mehta, Barry O'Sullivan, Vincent Vigneron. A Decomposition Approach for Discovering Discriminative Motifs in a Sequence Database. Frontiers in Artificial Intelligence and Applications, 2014, Prague, Czech Republic. pp.1057-1058, ⟨10.3233/978-1-61499-419-0-1057⟩. ⟨hal-03256765⟩

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