Using support vector machines for prediction of protein structural classes based on discrete wavelet transform
2008 Wiley Periodicals, Inc.
Publié dans: | Journal of computational chemistry. - 1984. - 30(2009), 8 vom: 20. Juni, Seite 1344-50 |
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Auteur principal: | |
Autres auteurs: | , , |
Format: | Article en ligne |
Langue: | English |
Publié: |
2009
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Accès à la collection: | Journal of computational chemistry |
Sujets: | Journal Article Research Support, Non-U.S. Gov't Proteins |
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 |
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Description: | Date Completed 14.07.2009 Date Revised 18.11.2010 published: Print Citation Status MEDLINE |
ISSN: | 1096-987X |
DOI: | 10.1002/jcc.21115 |