Prediction of protein residue contact using support vector machine

Prediction of protein residue contact is one of the important two-dimensional prediction tasks in protein structure prediction. The residue contact map of protein contains information which represents three-dimensional conformation of protein. However the accuracy of the prediction is dependent on t...

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Main Authors: Chan, Weng Howe, Mohammad, Mohd. Saberi
Format: Book Section
Published: Springer 2012
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Online Access:http://eprints.utm.my/id/eprint/35785/
http://dx.doi.org/10.1007/978-3-642-32826-8_33
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spelling my.utm.357852017-02-02T05:20:22Z http://eprints.utm.my/id/eprint/35785/ Prediction of protein residue contact using support vector machine Chan, Weng Howe Mohammad, Mohd. Saberi QA75 Electronic computers. Computer science Prediction of protein residue contact is one of the important two-dimensional prediction tasks in protein structure prediction. The residue contact map of protein contains information which represents three-dimensional conformation of protein. However the accuracy of the prediction is dependent on the type of protein information used to distinguish between contacts or non-contacts. According to CASP (Critical Assessment of Techniques of Protein Structure Prediction) the accuracy of protein contact map prediction is still low due to the behaviour of the predictors developed where the predictors only effective against specific type of protein structure. In order to further improve the performance of the predictor, effective features must be identified and used. Therefore, this research is conducted to determine the effectiveness of the existing features used in protein contact map prediction. Springer 2012 Book Section PeerReviewed Chan, Weng Howe and Mohammad, Mohd. Saberi (2012) Prediction of protein residue contact using support vector machine. In: Communications in Computer and Information Science. Springer, Berlin, pp. 323-332. ISBN 978-364232825-1 (Print); 978-364232826-8 (Electronic) http://dx.doi.org/10.1007/978-3-642-32826-8_33 DOI:10.1007/978-3-642-32826-8_33
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Chan, Weng Howe
Mohammad, Mohd. Saberi
Prediction of protein residue contact using support vector machine
description Prediction of protein residue contact is one of the important two-dimensional prediction tasks in protein structure prediction. The residue contact map of protein contains information which represents three-dimensional conformation of protein. However the accuracy of the prediction is dependent on the type of protein information used to distinguish between contacts or non-contacts. According to CASP (Critical Assessment of Techniques of Protein Structure Prediction) the accuracy of protein contact map prediction is still low due to the behaviour of the predictors developed where the predictors only effective against specific type of protein structure. In order to further improve the performance of the predictor, effective features must be identified and used. Therefore, this research is conducted to determine the effectiveness of the existing features used in protein contact map prediction.
format Book Section
author Chan, Weng Howe
Mohammad, Mohd. Saberi
author_facet Chan, Weng Howe
Mohammad, Mohd. Saberi
author_sort Chan, Weng Howe
title Prediction of protein residue contact using support vector machine
title_short Prediction of protein residue contact using support vector machine
title_full Prediction of protein residue contact using support vector machine
title_fullStr Prediction of protein residue contact using support vector machine
title_full_unstemmed Prediction of protein residue contact using support vector machine
title_sort prediction of protein residue contact using support vector machine
publisher Springer
publishDate 2012
url http://eprints.utm.my/id/eprint/35785/
http://dx.doi.org/10.1007/978-3-642-32826-8_33
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score 13.187197