Identifying discriminative classification-based motifs in biological sequences | Zendy

Celine Vens | Zendy; MarieNoëlle Rosso | Zendy; Étienne Danchin | Zendy

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Identifying discriminative classification-based motifs in biological sequences

Author(s) -

Celine Vens,

MarieNoëlle Rosso,

Étienne Danchin

Publication year - 2011

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr110

Subject(s) - computational biology , structural motif , biology , conserved sequence , sequence motif , proteome , sequence alignment , discriminative model , genetics , effector , peptide sequence , computer science , gene , artificial intelligence , biochemistry

Identification of conserved motifs in biological sequences is crucial to unveil common shared functions. Many tools exist for motif identification, including some that allow degenerate positions with multiple possible nucleotides or amino acids. Most efficient methods available today search conserved motifs in a set of sequences, but do not check for their specificity regarding to a set of negative sequences.

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