[1]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.
 LI Yuan - le and TAO Lan.Protein secondary structure prediction based on WSVM[J].Journal of Shenzhen University Science and Engineering,2006,23(2):117-121.
点击复制

基于小波核支持向量机的蛋白质二级结构预测()
分享到:

《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第23卷
期数:
2006年2期
页码:
117-121
栏目:
土木建筑工程
出版日期:
2006-04-30

文章信息/Info

Title:
Protein secondary structure prediction based on WSVM
文章编号:
1000-2618(2006)02-0117-05
作者:
李元乐陶兰
深圳大学信息工程学院,深圳 518060
Author(s):
LI Yuan - le and TAO Lan
College of Information Engineering, Shenzhen University, Shenzhen 518060, P. R. China
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
Keywords:
wavelet kernel function support vector machine protein secondary structure bioinformatics
分类号:
Q 617;TB 114
文献标志码:
A
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%.
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.

相似文献/References:

[1]陈文胜,徐晨.高维非平稳标准正交Semi-MRA的构造[J].深圳大学学报理工版,2005,22(2):159.
 CHEN Wen-sheng and XU Chen.A multi-dimensional nonstationary orthonormal Semi-multiresolutiion algorithm[J].Journal of Shenzhen University Science and Engineering,2005,22(2):159.

更新日期/Last Update: 2015-06-26