Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/99855
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dc.contributor.authorWang, Lipo.en
dc.contributor.authorYang, Zheng Rongen
dc.contributor.authorYoung, Natashaen
dc.contributor.authorTrudgian, Daveen
dc.contributor.authorChou, Kuo-Chenen
dc.date.accessioned2012-05-22T03:00:42Zen
dc.date.accessioned2019-12-06T20:12:22Z-
dc.date.available2012-05-22T03:00:42Zen
dc.date.available2019-12-06T20:12:22Z-
dc.date.copyright2005en
dc.date.issued2005en
dc.identifier.citationYang, Z. R., Wang, L., Young, N., Trudgian, D., & Chou, K. C. (2005). Pattern recognition methods for protein functional site prediction. Current Protein & Peptide Science, 6(5), 479-491.en
dc.identifier.issn1389-2037en
dc.identifier.urihttps://hdl.handle.net/10356/99855-
dc.description.abstractProtein functional site prediction is closely related to drug design, hence to public health. In order to save the cost and the time spent on identifying the functional sites in sequenced proteins in biology laboratory, computer programs have been widely used for decades. Many of them are implemented using the state-of-the-art pattern recognition algorithms, including decision trees, neural networks and support vector machines. Although the success of this effort has been obvious, advanced and new algorithms are still under development for addressing some difficult issues. This review will go through the major stages in developing pattern recognition algorithms for protein functional site prediction and outline the future research directions in this important area.en
dc.language.isoenen
dc.relation.ispartofseriesCurrent protein & peptide scienceen
dc.rights© 2005 Bentham Science Publishers.en
dc.subjectDRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognitionen
dc.titlePattern recognition methods for protein functional site predictionen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.identifier.openurlhttp://www.benthamdirect.org/pages/content.php?CPPS/2005/00000006/00000005/0009Ken
item.grantfulltextnone-
item.fulltextNo Fulltext-
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