Comparative accuracy of methods for protein sequence similarity search. | Zendy

Pankaj Agarwal | Zendy; David J. States | Zendy

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Comparative accuracy of methods for protein sequence similarity search.

Author(s) -

Pankaj Agarwal,

David J. States

Publication year - 1998

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/14.1.40

Subject(s) - similarity (geometry) , sequence (biology) , computer science , sequence alignment , computational biology , data mining , artificial intelligence , biology , peptide sequence , genetics , gene , image (mathematics)

Searching a protein sequence database for homologs is a powerful tool for discovering the structure and function of a sequence. Two new methods for searching sequence databases have recently been described: Probabilistic Smith-Waterman (PSW), which is based on Hidden Markov models for a single sequence using a standard scoring matrix, and a new version of BLAST (WU-BLAST2), which uses Sum statistics for gapped alignments.

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