Estimating the significance of sequence order in protein secondary structure prediction.

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dc.contributor.authorjong parkko
dc.contributor.authorsabine dietmannko
dc.contributor.authorandreas hegerko
dc.contributor.authorliisa holmko
dc.date.accessioned2013-02-27T22:21:52Z-
dc.date.available2013-02-27T22:21:52Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2000-
dc.identifier.citationBIOINFORMATICS, v.16, no.11, pp.978 - 987-
dc.identifier.issn1367-4803-
dc.identifier.urihttp://hdl.handle.net/10203/71179-
dc.description.abstractMotivation: How critical is the sequence order information in predicting protein secondary structure segments? We tried to get a rough insight on it from a theoretical approach using both a prediction algorithm and structural fragments from Protein Databank (PDB). Results: Using reverse protein sequences and PDB structural fragments, we theoretically estimated the significance of the order for protein secondary structure and prediction. On average: (1) 79% of protein sequence segments resulted in the same prediction in both normal and reverse directions, which indicated a relatively high conservation of secondary structure propensity in the reverse direction; (2) the reversed sequence prediction alone performed less accurately than the normal forward sequence prediction, but comparably high (2% difference); (3) the commonly predicted regions showed a slightly higher prediction accuracy (4%) than the normal sequences prediction; and (4) structural fragments which have counterparts in reverse direction in the same protein showed a comparable degree of secondary structure conservation (73% identity with reversed structures on average for pentamers).-
dc.languageEnglish-
dc.publisherOxford Univ Press-
dc.subjectFOLD RECOGNITION-
dc.subjectGLOBULAR-PROTEINS-
dc.subjectALIGNMENT-
dc.subjectIDENTIFICATION-
dc.subjectDATABASE-
dc.subjectACCURACY-
dc.subjectIMPROVEMENTS-
dc.subjectPERFORMANCE-
dc.subjectPARAMETERS-
dc.subjectHOMOLOGY-
dc.titleEstimating the significance of sequence order in protein secondary structure prediction.-
dc.typeArticle-
dc.identifier.wosid000166343700004-
dc.identifier.scopusid2-s2.0-0034521885-
dc.type.rimsART-
dc.citation.volume16-
dc.citation.issue11-
dc.citation.beginningpage978-
dc.citation.endingpage987-
dc.citation.publicationnameBIOINFORMATICS-
dc.identifier.doi10.1093/bioinformatics/16.11.978-
dc.contributor.localauthorjong park-
dc.contributor.nonIdAuthorsabine dietmann-
dc.contributor.nonIdAuthorandreas heger-
dc.contributor.nonIdAuthorliisa holm-
dc.type.journalArticleArticle-
dc.subject.keywordPlusFOLD RECOGNITION-
dc.subject.keywordPlusGLOBULAR-PROTEINS-
dc.subject.keywordPlusALIGNMENT-
dc.subject.keywordPlusIDENTIFICATION-
dc.subject.keywordPlusDATABASE-
dc.subject.keywordPlusACCURACY-
dc.subject.keywordPlusIMPROVEMENTS-
dc.subject.keywordPlusPERFORMANCE-
dc.subject.keywordPlusPARAMETERS-
dc.subject.keywordPlusHOMOLOGY-
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