COACH: profile–profile alignment of protein families using hidden Markov models | Zendy

R. C. Edgar | Zendy; Kimmen Sjölander | Zendy

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COACH: profile–profile alignment of protein families using hidden Markov models

Author(s) -

R. C. Edgar,

Kimmen Sjölander

Publication year - 2004

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/bth091

Subject(s) - hidden markov model , multiple sequence alignment , sequence (biology) , computer science , sequence alignment , sensitivity (control systems) , markov chain , pattern recognition (psychology) , alignment free sequence analysis , artificial intelligence , data mining , algorithm , machine learning , biology , genetics , engineering , peptide sequence , electronic engineering , gene

Alignments of two multiple-sequence alignments, or statistical models of such alignments (profiles), have important applications in computational biology. The increased amount of information in a profile versus a single sequence can lead to more accurate alignments and more sensitive homolog detection in database searches. Several profile-profile alignment methods have been proposed and have been shown to improve sensitivity and alignment quality compared with sequence-sequence methods (such as BLAST) and profile-sequence methods (e.g. PSI-BLAST). Here we present a new approach to profile-profile alignment we call Comparison of Alignments by Constructing Hidden Markov Models (HMMs) (COACH). COACH aligns two multiple sequence alignments by constructing a profile HMM from one alignment and aligning the other to that HMM.

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