Two-stage support vector machines for protein structure and solvent prediction

We 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 informati...

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Bibliographic Details
Main Author:	Nguyen, Ngoc Minh
Other Authors:	Jagath C. Rajapakse
Format:	Theses and Dissertations
Published:	2008
Subjects:	DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences
Online Access:	https://hdl.handle.net/10356/2407
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Institution:	Nanyang Technological University

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spelling	sg-ntu-dr.10356-24072023-03-04T00:39:17Z Two-stage support vector machines for protein structure and solvent prediction Nguyen, Ngoc Minh Jagath C. Rajapakse School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences We 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. DOCTOR OF PHILOSOPHY(SCE) 2008-09-17T09:02:25Z 2008-09-17T09:02:25Z 2005 2005 Thesis Nguyen, N. M. (2005). Two-stage support vector machines for protein structure and solvent prediction. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/2407 10.32657/10356/2407 Nanyang Technological University application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
topic	DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences
spellingShingle	DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences Nguyen, Ngoc Minh Two-stage support vector machines for protein structure and solvent prediction
description	We 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.
author2	Jagath C. Rajapakse
author_facet	Jagath C. Rajapakse Nguyen, Ngoc Minh
format	Theses and Dissertations
author	Nguyen, Ngoc Minh
author_sort	Nguyen, Ngoc Minh
title	Two-stage support vector machines for protein structure and solvent prediction
title_short	Two-stage support vector machines for protein structure and solvent prediction
title_full	Two-stage support vector machines for protein structure and solvent prediction
title_fullStr	Two-stage support vector machines for protein structure and solvent prediction
title_full_unstemmed	Two-stage support vector machines for protein structure and solvent prediction
title_sort	two-stage support vector machines for protein structure and solvent prediction
publishDate	2008
url	https://hdl.handle.net/10356/2407
_version_	1759857182207115264

Two-stage support vector machines for protein structure and solvent prediction

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