dc.contributor.authorNguyen, Ngoc Minhen_US
dc.date.accessioned2008-09-17T09:02:25Z
dc.date.accessioned2017-07-23T08:28:15Z
dc.date.available2008-09-17T09:02:25Z
dc.date.available2017-07-23T08:28:15Z
dc.date.copyright2005en_US
dc.date.issued2005
dc.identifier.citationNguyen, N. M. (2005). Two-stage support vector machines for protein structure and solvent prediction. Doctoral thesis, Nanyang Technological University, Singapore.
dc.identifier.urihttp://hdl.handle.net/10356/2407
dc.description.abstractWe propose Two-Stage Support Vector Machines (TSSVM) for the prediction of structural properties of amino acid residues, namely, relative solvent accessibilities and protein secondary structure elements. The second stage of TSSVM extends the classical SVM approach to capture the contextual information among the secondary structural elements or the relative solvent accessibilities and thereby improves the accuracies of the predictions.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences
dc.titleTwo-stage support vector machines for protein structure and solvent predictionen_US
dc.typeThesisen_US
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.contributor.supervisorJagath C. Rajapakse (SCSE)en_US
dc.description.degreeDOCTOR OF PHILOSOPHY(SCE)en_US


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