Radial basis function method for prediction of protein secondary structure

被引：0

作者：

Zhang, Zhen ^{[1
,2
]}

Jing, Nan ^{[3
]}

机构：

[1] South China Univ Technol, Dept Comp Sci, Guangzhou 510641, Peoples R China

[2] Jinan Univ, Dept Comp Sci, Guangzhou 510632, Guangdong, Peoples R China

[3] South China Univ Technol, Coll E Bussiness, Guangzhou 510006, Guangdong, Peoples R China

来源：

PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2008年

关键词：

radial basis function neural networks; protein secondary structure; evolutionary information; amino acids sequence;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The paper proposed a new method based on radial basis function neural networks for prediction of protein secondary structure. To make the algorithm comparable to other secondary structure prediction methods, we used the benchmark evaluation data set of 126 protein chains in this paper. We also analyzed how to use evolutionary information to enhance the prediction accuracy. The paper discussed the influence of data selection and structure design on the performance of the networks. The results indicate that this method is feasible and effective.

引用

页码：1379 / +

页数：2

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