Consensus RNA secondary structure prediction based on SVMs

摘要：

Although many endeavors have been done in the field of RNA secondary structure prediction, it is still an open problem in the computational molecular biology. The comparative sequence analysis is the golden standard method when given homologous sequence alignment. The essential of this method can be regarded as classifier problem: to judge whether any two columns of an alignment correspond to a base pair using provided information by alignment. Here, we employ SVMs to resolve this classifier problem, and select the covaration score, the fraction of complementary nucleotides and the consensus probability matrix as the feature vectors. Test on the Rfam shows that average MCC of our method is higher (0.841) than KnetFold (0.831), Pfold (0.741) and RNAalifold(0.623).

关键词： RNA secondary structure classifier problem SVM

作者: Zhao Yingjie Wang Zhengzhi

作者单位: College of Mechatronics Engineering and Automation National University of Defense Technology Changsha, 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: 101-104

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）