DLocalMotif: a discriminative approach for discovering local motifs in protein sequences | Zendy

Ahmed M. Mehdi | Zendy; Muhammad Shoaib B. Sehgal | Zendy; Boštjan Kobe | Zendy; Timothy L. Bailey | Zendy; Mikael Bodén | Zendy

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DLocalMotif: a discriminative approach for discovering local motifs in protein sequences

Author(s) -

Ahmed M. Mehdi,

Muhammad Shoaib B. Sehgal,

Boštjan Kobe,

Timothy L. Bailey,

Mikael Bodén

Publication year - 2012

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/bts654

Subject(s) - discriminative model , computer science , computational biology , artificial intelligence , pattern recognition (psychology) , machine learning , biology

Local motifs are patterns of DNA or protein sequences that occur within a sequence interval relative to a biologically defined anchor or landmark. Current protein motif discovery methods do not adequately consider such constraints to identify biologically significant motifs that are only weakly over-represented but spatially confined. Using negatives, i.e. sequences known to not contain a local motif, can further increase the specificity of their discovery.

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