Sequence search algorithm assessment and testing toolkit (SAT) | Zendy

Jong Moon Park | Zendy; Liisa Holm | Zendy; Cyrus Chothia | Zendy

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Sequence search algorithm assessment and testing toolkit (SAT)

Author(s) -

Jong Moon Park,

Liisa Holm,

Cyrus Chothia

Publication year - 2000

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/16.2.104

Subject(s) - computer science , sequence database , file transfer protocol , parsing , algorithm , sequence (biology) , database , r package , data mining , information retrieval , programming language , world wide web , the internet , genetics , biology , gene , biochemistry , chemistry

The Sequence Search Algorithm Assessment and Testing Toolkit (SAT) aims to be a complete package for the comparison of different protein homology search algorithms. The structural classification of proteins can provide us with a clear criterion for judgment in homology detection. There have been several assessments based on structural sequences with classifications but a good deal of similar work is now being repeated with locally developed procedures and programs. The SAT will provide developers with a complete package which will save time and produce more comparable performance assessments for search algorithms. The package is complete in the sense that it provides a non-redundant large sequence resource database, a well-characterized query database of proteins domains, all the parsers and some previous results from PSI-BLAST and a hidden markov model algorithm.

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