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Communication Dans Un Congrès Année : 2014

A Decomposition Approach for Discovering Discriminative Motifs in a Sequence Database

Deepak Mehta
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Barry O'Sullivan
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Résumé

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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Dates et versions

hal-03256765 , version 1 (10-06-2021)

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Citer

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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