DC Field | Value | Language |
---|---|---|
dc.contributor.author | jong park | ko |
dc.contributor.author | liisa holm | ko |
dc.contributor.author | cyrus chothia | ko |
dc.date.accessioned | 2013-02-28T03:14:55Z | - |
dc.date.available | 2013-02-28T03:14:55Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2000-02 | - |
dc.identifier.citation | BIOINFORMATICS, v.16, no.2, pp.104 - 110 | - |
dc.identifier.issn | 1367-4803 | - |
dc.identifier.uri | http://hdl.handle.net/10203/72475 | - |
dc.description.abstract | Motivation: 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 judgement in homology detection. There have been several assessments based on structural sequences with classifications but a good deal of similar work is now being repented 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. Results: An analysis on two different data sets was carried out using the SAT package. It compared rite performance of a full protein sequence database (RSDB100) with a non-redundant representative sequence database derived from it (RSDB50). The performance measurement indicated that the full database is sub-optimal for a homology search. This result justifies the use of much smaller and faster RSDB50 than RSDB100 for the SAT. | - |
dc.language | English | - |
dc.publisher | Oxford Univ Press | - |
dc.subject | HIDDEN MARKOV-MODELS | - |
dc.subject | PROTEIN DATABASE | - |
dc.subject | ALIGNMENT | - |
dc.title | Sequence Search Algorithm Assessment and Testing Toolkit (SAT) | - |
dc.type | Article | - |
dc.identifier.wosid | 000087033600005 | - |
dc.identifier.scopusid | 2-s2.0-0034102579 | - |
dc.type.rims | ART | - |
dc.citation.volume | 16 | - |
dc.citation.issue | 2 | - |
dc.citation.beginningpage | 104 | - |
dc.citation.endingpage | 110 | - |
dc.citation.publicationname | BIOINFORMATICS | - |
dc.identifier.doi | 10.1093/bioinformatics/16.2.104 | - |
dc.contributor.localauthor | jong park | - |
dc.contributor.nonIdAuthor | liisa holm | - |
dc.contributor.nonIdAuthor | cyrus chothia | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordPlus | HIDDEN MARKOV-MODELS | - |
dc.subject.keywordPlus | PROTEIN DATABASE | - |
dc.subject.keywordPlus | ALIGNMENT | - |
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