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Protein secondary structure prediction using sequence profile and conserved domain profile

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dc.contributor.authorWoo, SK-
dc.contributor.authorPark, CB-
dc.contributor.authorLee, SW-
dc.date.accessioned2021-09-09T06:57:34Z-
dc.date.available2021-09-09T06:57:34Z-
dc.date.created2021-06-19-
dc.date.issued2005-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/123268-
dc.description.abstractIn this paper, we proposed a novel method for protein secondary structure prediction using sequence profile and conserved domain profile. Sequence profile generated from PSI-BLAST (position specific iterated BLAST) has been widely used in protein secondary structure prediction, because PSI-BLAST shows good performance in finding remote homology. Conserved domains kept functional and structural information of related proteins; therefore we could draw remote homology information in conserved domains using RPS-BLAST (reverse position specific BLAST). We combined sequence profile and conserved domain profile to get more remote homology information, and propose a method which used the combined profile to predict the protein secondary structures. In order to verify the effectiveness of our proposed method, we implemented a protein secondary structure prediction system. Overall prediction accuracy reached 75.9% on the RS126 data set. The improvement by incorporating conserved domain information exceeded 3%, and this result showed that our proposed method could improve significantly the accuracy of protein secondary structure prediction.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.titleProtein secondary structure prediction using sequence profile and conserved domain profile-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, SW-
dc.identifier.wosid000232529000001-
dc.identifier.bibliographicCitationADVANCES IN INTELLIGENT COMPUTING, PT 2, PROCEEDINGS, v.3645, pp.1 - 10-
dc.relation.isPartOfADVANCES IN INTELLIGENT COMPUTING, PT 2, PROCEEDINGS-
dc.citation.titleADVANCES IN INTELLIGENT COMPUTING, PT 2, PROCEEDINGS-
dc.citation.volume3645-
dc.citation.startPage1-
dc.citation.endPage10-
dc.type.rimsART-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
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