期刊
JOURNAL OF COMPUTATIONAL CHEMISTRY
卷 30, 期 8, 页码 1344-1350出版社
JOHN WILEY & SONS INC
DOI: 10.1002/jcc.21115
关键词
protein structural class; discrete wavelet transform; support vector machines; hydrophobicity; cross-validation
资金
- National Natural Science Foundation of China [20605010]
- Opening Foundation of State Key Laboratory of Chem/Biosensing and Chemometrics of Hunan University [2006022]
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. (C) 2008 Wiley Periodicals, Inc. J Comput Chem 30: 1344-1350, 2009
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