Parameters Optimization of Support Vector Machine for Discriminating Thermophilic and Mesophilic Enzyme

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Parameters Optimization of Support Vector Machine for Discriminating Thermophilic and Mesophilic Enzyme
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It was widely accepted that amino acid composition play vital role on the protein thermostability.In this manuscript,20-amino acid composition in their protein sequence was chosen as the feature vector of SVM and used to predict the protein thermostability by SVM.the accuracy increased from 85.4% to 88.2% by using the geometrical method to optimize SVM parameter.Furthermore,it could be acquired following conclusions:(1) geometrical method is an efficient method to improve the accuracy of SVM parameters;.(2) there is a very close relationship between percentage of amino acid and enzyme thermostability.

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ZHANG Zheng-yang, XU Wen-bo, DING Yan-rui. Parameters Optimization of Support Vector Machine for Discriminating Thermophilic and Mesophilic Enzyme[J]. Journal of Food Science and Biotechnology,2010,29(2):312-316.

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Online: June 17,2014
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