Predict the Tertiary Strulcture of Protein with Error-Correcting Output Coding and Flexible Neural Tree

摘要：

　　In this paper we intend to apply a new method to predict tertiary structure.A novel hybrid feature adopted is composed of physicochemicai composition (PCC),recurrence quantification analysis (RQA) and pseudo amino acid composition (PseAA).We use the Error Correcting Output Coding (ECOC) based on three flexible neural tree models as the classifiers.640 dataset is selected to our experiment.The predict accuracy with our method on this data set is 60.23%,higher than some other methods on the 640 datasets.So,our method is feasible and effective in some extent.

关键词： tertiary structure feature extraction ECOC FNT

作者: Yiming Chen Yuehui Chen

作者单位: School of Information science and Engineering, University of Jinan Jinan,PR China

会议类型: 国际会议

会议名称: 2012 2nd International Conference on Computer and Information Applications(ICCIA2012)(2012第二届计算机和信息应用国际会议)

会议地点: 太原

会议语种:英文

页码: 230-232

在线出版日期: 2012-12-08（万方平台首次上网日期，不代表论文的发表时间）