| 基于小波核支持向量机的蛋白质二级结构预测 |
| |
| 引用本文： | 李元乐,陶兰. 基于小波核支持向量机的蛋白质二级结构预测[J]. 深圳大学学报(理工版), 2006, 23(2): 117-121 |
| |
| 作者姓名： | 李元乐 陶兰 |
| |
| 作者单位： | 深圳大学信息工程学院,深圳,518060 |
| |
| 摘 要： | 提出一种基于小波核支持向量机分类模型,将其用于SARS蛋白质二级结构预测.实验表明,该模型与其他同类方法相比,提高蛋白质二级结构预测的准确度达到1%～2%.
|
| 关 键 词： | 小波 核函数 支持向量机 蛋白质二级结构预测 生物信息学 |
| 文章编号： | 1000-2618(2006)02-0117-05 |
| 收稿时间： | 2005-12-06 |
| 修稿时间： | 2006-03-07 |
Protein secondary structure prediction based on WSVM |
| |
| LI Yuan-le,TAO Lan. Protein secondary structure prediction based on WSVM[J]. Journal of Shenzhen University(Science &engineering), 2006, 23(2): 117-121 |
| |
| Authors: | LI Yuan-le TAO Lan |
| |
| Affiliation: | College of Information Engineering Shenzhen University Shenzhen 518060 P. R. China |
| |
| Abstract: | A classification model based on the wavelet kernel function of support vector machine(SVM) was proposed to improve the accuracy of protein secondary structure prediction.The model was applied to predict protein secondary structure of SRAS.It shows good abilities of classification and generalization by making use of the characters of wavelet and SVM.Simulational results show that the algorithm has better performance than other comparable ones and that it can improve the accuracy of predicting secondary structure of SARS by a 1%~2% increase. |
| |
| Keywords: | wavelet kernel function support vector machine protein secondary, structure bioinformatics |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
