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Fuzzy k-nearest neighbor method for protein secondary structure prediction and its parallel implementation

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dc.contributor.authorKim, Seung-Yeon-
dc.contributor.authorSim, Jaehyun-
dc.contributor.authorLee, Julian-
dc.date.available2019-04-10T11:37:23Z-
dc.date.created2018-04-17-
dc.date.issued2006-08-
dc.identifier.isbn3540372776-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/33875-
dc.description.abstractFuzzy k-nearest neighbor method is a generalization of nearest neighbor method, the simplest algorithm for pattern classification. One of the important areas for application of the pattern classification is the protein secondary structure prediction, an important topic in the field of bioinformatics. In this work, we develop a parallel algorithm for protein secondary structure prediction, based on the fuzzy k-nearest neighbor method, that uses evolutionary profile obtained from PSI-BLAST (Position Specific Iterative Basic Local Sequence Alignment Tool) as the feature vectors.-
dc.language영어-
dc.language.isoen-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.relation.isPartOfCOMPUTATIONAL INTELLIGENCE AND BIOINFORMATICS, PT 3, PROCEEDINGS-
dc.titleFuzzy k-nearest neighbor method for protein secondary structure prediction and its parallel implementation-
dc.typeConference-
dc.type.rimsCONF-
dc.identifier.bibliographicCitationInternational Conference on Intelligent Computing, ICIC 2006, v.4115, pp.444 - 453-
dc.description.journalClass2-
dc.identifier.wosid000240085400048-
dc.identifier.scopusid2-s2.0-33749575594-
dc.citation.conferenceDate2006-08-16-
dc.citation.conferencePlaceGE-
dc.citation.conferencePlaceKunming-
dc.citation.endPage453-
dc.citation.startPage444-
dc.citation.titleInternational Conference on Intelligent Computing, ICIC 2006-
dc.citation.volume4115-
dc.contributor.affiliatedAuthorLee, Julian-
dc.type.docTypeArticle; Proceedings Paper-
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