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A Prediction Method of Protein Disulfide Bond Based on Hybrid Strategy

A Prediction Method of Protein Disulfide Bond Based on Hybrid Strategy
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摘要 A prediction method of protein disulfide bond based on support vector machine and sample selection is proposed in this paper. First, the protein sequences selected are en-coded according to a certain encoding, input data for the prediction model of protein disulfide bond is generated;Then sample selection technique is used to select a portion of input data as training samples of support vector machine;finally the prediction model training samples trained is used to predict protein disulfide bond. The result of simulation experiment shows that the prediction model based on support vector ma-chine and sample selection can increase the prediction accuracy of protein disulfide bond. A prediction method of protein disulfide bond based on support vector machine and sample selection is proposed in this paper. First, the protein sequences selected are en-coded according to a certain encoding, input data for the prediction model of protein disulfide bond is generated;Then sample selection technique is used to select a portion of input data as training samples of support vector machine;finally the prediction model training samples trained is used to predict protein disulfide bond. The result of simulation experiment shows that the prediction model based on support vector ma-chine and sample selection can increase the prediction accuracy of protein disulfide bond.
作者 Pengfei Sun Yunhong Ding Yuyan Huang Lei Zhang Pengfei Sun;Yunhong Ding;Yuyan Huang;Lei Zhang(College of Computer Science and Technology, Harbin Normal University, Harbin, China)
出处 《Journal of Biomedical Science and Engineering》 2016年第10期116-121,共6页 生物医学工程(英文)
关键词 Disulfide Bond Support Vector Machine Sample Selection Disulfide Bond Support Vector Machine Sample Selection
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