Protein Secondary Structure Prediction Using AutoEncoder Network and Bayes Classifier

摘要：

　　Protein secondary structure prediction is belong to bioinformatics,and its important in research area.In this paper,we propose a new prediction way of protein using bayes classifier and autoEncoder network.Our experiments show some algorithms including the construction of the model,the classification of parameters and so on.The data set is a typical CB513 data set for protein.In terms of accuracy,the method is the cross validation based on the 3-fold.Then we can get the Q3 accuracy.Paper results illustrate that the autoencoder network improved the prediction accuracy of protein secondary structure.

作者: Leilei Wang Jinyong Cheng

作者单位: College of Information,Qilu University of Technology(Shandong Academy of Sciences),Jinan,China

会议类型: 国际会议

会议名称: 2017 International Symposium on Application of Materials Science and Energy Materials (SAMSE 2017) (2017材料科学应用与能源材料国际研讨会)

会议地点: 上海

会议语种:英文

页码: 1-4

在线出版日期: 2017-12-28（万方平台首次上网日期，不代表论文的发表时间）