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  • Title: Using support vector machines for prediction of protein structural classes based on discrete wavelet transform.
    Author: Qiu JD, Luo SH, Huang JH, Liang RP.
    Journal: J Comput Chem; 2009 Jun; 30(8):1344-50. PubMed ID: 19009604.
    Abstract:
    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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