Protein Secondary Structure Prediction Using SVM with Bayesian Method

摘要：

Prediction of protein secondary structures is an important problem in bioinformatics and has many applications. The recent trend of secondary structure prediction studies is mostly based on the neural network or the support vector machine (SVM). In the paper, a two stage predictor is constructed to predict protein secondary structures. The first stage consists of one predictor based on the support vector machine. Bayesian discrimination is used at the second stage by considering the predicted labels of neighbor residues. The improvement of prediction performances exploits that residues tend to form structures cluster. This method outperforms the predictors based on SVM algorithm alone. Our proposed approach is promising which can be verified by its better prediction performance based on a non-redundant data set.

关键词： protein secondary structures support vector machine Bayesian Method

作者: Wen Yuan Liu Shui Xing Wang Bao Wen Wang Jia Xin Yu

作者单位: College of Information Science and Engineering, Yanshan University. Qin huangdao,China

会议类型: 国际会议

会议名称: The 2nd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2008)(第二届生物信息与生物医学工程国际会议)

会议地点: 上海

会议语种:英文

页码: 279-281

在线出版日期: 2008-05-16（万方平台首次上网日期，不代表论文的发表时间）