A Decomposition Approach for Discovering Discriminative Motifs in a Sequence Database - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

A Decomposition Approach for Discovering Discriminative Motifs in a Sequence Database

(1) , , , (1)
1
Deepak Mehta
  • Fonction : Auteur
Barry O'Sullivan
  • Fonction : Auteur
  • PersonId : 849989

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.
Fichier principal
Vignette du fichier
2014lesaintecai.pdf (155.66 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

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

Identifiants

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⟩

Collections

UNIV-ANGERS LERIA
12 Consultations
23 Téléchargements

Altmetric

Partager

Gmail Facebook Twitter LinkedIn More