Voting for the Prediction of Protein Secondary Structure and Its Evaluation

摘要：

Protein secondary structure prediction is one of the central topics in proteome analysis. Computational methods, developed for the prediction (classification) of protein secondary structures, have been improved substantially since 1990s, allowing us to investigate some of the computational classifiers and attempt to integrate them through voting. The study tries to evaluate whether and how much voting can improve the prediction accuracy. In the research, 4 classifiers (i.e. predictors), SSpro, PSIpred, PHD and Prof, are selected since they produce some reasonably good prediction accuracies. Two voting methods are adopted to integrate these 4 classifiers-a simple majority voting by assigning data to a class that gains the majority votes, and a weighted majority voting which weights each vote by the prediction accuracy of the classifiers. The voting results show that including better-performed classifiers tends to improve the prediction while including poor-performed classifiers tend to deteriorate the prediction. More investigation could be carried out using more classifiers or more diverse classifiers in a future research.

关键词： protein secondary structure prediction classification voting

作者: Ying-Song Dong Zhi-Song He Zi-Liang Qian Yu-Dong Cai

作者单位: Department of Life Science and Technology,HuaZhong University of Science and Technology,1037 Luoyu R Department of Bioinformatics,College of Life Sciences,Zhejiang University,HangZhou,ZheJiang,310058,C Bioinformatics Center,Shanghai Institutes for Biological Sciences,Chinese Academy of Sciences,320 Yu Institute of System Biology,Shanghai University,99 ShangDa Road,Shanghai,200244,China Department of

会议类型: 国际会议

会议名称: The 3rd International Symposium on Optimization and System Biology(第三届最优化与系统生物学国际会议 OSB09)

会议地点: 张家界

会议语种:英文

页码: 17-24

在线出版日期: 2009-09-20（万方平台首次上网日期，不代表论文的发表时间）