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ISMB
1997

Enumerating and Ranking Discrete Motifs

14 years 24 days ago
Enumerating and Ranking Discrete Motifs
Discrete motifsthat discriminate functionalclasses of proteins are useful for classifying newsequences, capturingstructural constraints, andidentifyingprotein subclasses.Despitethe fact that the spaceof suchmotifs can grow exponentially with sequence length and number,weshowthat in practice it usuallydoesnot, and wedescribea techniquethat infers motifsfromaligned protein sequencesby exhaustivelysearchingthis space. Ourmethodgeneratessequencemotifsover a widerange of recall andprecision,andchoosesa representativemotif basedon a scorethat wederivefrombothstatistical and information-theoreticframeworks.Finally, weshowthat the selected motifsperformwell in practice, classifying unseensequenceswith extremely high precision, and infer protein subclasses that correspond to known biochemicalclasses.
Craig G. Nevill-Manning, Komal S. Sethi, Thomas D.
Added 01 Nov 2010
Updated 01 Nov 2010
Type Conference
Year 1997
Where ISMB
Authors Craig G. Nevill-Manning, Komal S. Sethi, Thomas D. Wu, Douglas L. Brutlag
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