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A generalized affine gap model significantly improves protein sequence alignment accuracy
Author(s) -
Zachariah Marcus A.,
Crooks Gavin E.,
Holbrook Stephen R.,
Brenner Steven E.
Publication year - 2004
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.20299
Subject(s) - affine transformation , homology modeling , sequence alignment , homology (biology) , multiple sequence alignment , computer science , sequence (biology) , computational biology , sequence homology , mathematics , artificial intelligence , biology , genetics , peptide sequence , pure mathematics , amino acid , gene , biochemistry , enzyme
Sequence alignment underpins common tasks in molecular biology, including genome annotation, molecular phylogenetics, and homology modeling. Fundamental to sequence alignment is the placement of gaps, which represent character insertions or deletions. We assessed the ability of a generalized affine gap cost model to reliably detect remote protein homology and to produce high‐quality alignments. Generalized affine gap alignment with optimal gap parameters performed as well as the traditional affine gap model in remote homology detection. Evaluation of alignment quality showed that the generalized affine model aligns fewer residue pairs than the traditional affine model but achieves significantly higher per‐residue accuracy. We conclude that generalized affine gap costs should be used when alignment accuracy carries more importance than aligned sequence length. Proteins 2005. © 2004 Wiley‐Liss, Inc.