A SVM BASED APPROACH FOR MIRNA TARGET PREDICTION

摘要：

MicroRNAs (miRNAs) are short RNAs that play important roles in post-transcriptionally regulation by binding to the target mRNAs. Although for a large number of animals□ miRNAs have been defined, only a few targets have been known. Here we present a naive microRNA target prediction algorithm based on machine learning approach. SVM was used twice in our algorithm in order to make prediction for binding site and mRINA respectively. In order to avoid the loss of sensitivity, a set of seed match rules were defined base on observing experimentally validated targets to locate potential sites in 3(玀)TR sequences. TarBase and microarray data were used to build up database for training and evaluation of our algorithm. TargetScan and miRanda were implemented for comparison. The result shows that the performance of our algorithm is better than TargetScan and miRanda.

关键词： SVM miRNA Target prediction

作者: HUI LIU DONG YUE LIN ZHANG YU-FEI HUANG

作者单位: SIEE, China University of Mining and Technology, Xuzhou, Jiangsu 221008, China Dept.of ECE, University of Texas at San Antonio San Antonio, TX 78249 Dept.of ECE, University of Texas at San Antonio San Antonio, TX 78249 Greehey Childrens Cancer Rese

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 4007-4011

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）