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dc.contributor.authorChang, Jyh-Yeongen_US
dc.contributor.authorShyu, Jia-Jieen_US
dc.contributor.authorShi, Yi-Xiangen_US
dc.date.accessioned2014-12-08T15:49:04Z-
dc.date.available2014-12-08T15:49:04Z-
dc.date.issued2008en_US
dc.identifier.isbn978-3-540-69159-4en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/11536/32608-
dc.description.abstractThe prediction of protein solvent accessibility is an intermediate step for predicting the tertiary structure of proteins. Knowledge of solvent accessibility has proved useful for identifying protein function, sequence motifs, and domains. Using a position-specific scoring matrix (PSSM) generated from PSI-BLAST in this paper, we develop the modified fuzzy k-nearest neighbor method to predict the protein relative solvent accessibility. By modifying the membership functions of the fuzzy k-nearest neighbor method by Sim et al. [1], has recently been applied to protein solvent accessibility prediction with excellent results. Our modified fuzzy k-nearest neighbor method is applied on the three-state, E, I, and B, and two-state, E, and B, relative solvent accessibility predictions, and its prediction accuracy compares favorly with those by the fuzzy k-NN and other approaches.en_US
dc.language.isoen_USen_US
dc.titleFuzzy k-nearest neighbor classifier to predict protein solvent accessibilityen_US
dc.typeProceedings Paperen_US
dc.identifier.journalNEURAL INFORMATION PROCESSING, PART IIen_US
dc.citation.volume4985en_US
dc.citation.spage837en_US
dc.citation.epage845en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000257315300087-
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