Using support vector machines for prediction of protein structural classes based on discrete wavelet transform

2008 Wiley Periodicals, Inc.

Détails bibliographiques
Publié dans:Journal of computational chemistry. - 1984. - 30(2009), 8 vom: 20. Juni, Seite 1344-50
Auteur principal: Qiu, Jian-Ding (Auteur)
Autres auteurs: Luo, San-Hua, Huang, Jian-Hua, Liang, Ru-Ping
Format: Article en ligne
Langue:English
Publié: 2009
Accès à la collection:Journal of computational chemistry
Sujets:Journal Article Research Support, Non-U.S. Gov't Proteins
Description
Résumé:2008 Wiley Periodicals, Inc.
The prediction of secondary structure is a fundamental and important component in the analytical study of protein structure and functions. How to improve the predictive accuracy of protein structural classification by effectively incorporating the sequence-order effects is an important and challenging problem. In this study, a new method, in which the support vector machine combines with discrete wavelet transform, is developed to predict the protein structural classes. Its performance is assessed by cross-validation tests. The predicted results show that the proposed approach can remarkably improve the success rates, and might become a useful tool for predicting the other attributes of proteins as well
Description:Date Completed 14.07.2009
Date Revised 18.11.2010
published: Print
Citation Status MEDLINE
ISSN:1096-987X
DOI:10.1002/jcc.21115