LncTar: a tool for predicting the RNA targets of long noncoding RNAs

Jianwei Li(Peking University), Wei Ma(Hebei University of Technology), Pan Zeng(Hebei University of Technology), Junyi Wang(Hebei University of Technology), Bin Geng(Hebei University of Technology), Jichun Yang(Peking University), Qinghua Cui(Peking University)
Briefings in Bioinformatics
December 17, 2014
Cited by 491Open Access
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Abstract

Long noncoding RNAs (lncRNAs) represent a big category of noncoding RNA molecules, and increasing studies have shown that they play important roles in various critical biological processes. They show a diversity of functions through diverse mechanisms, among which regulating RNA molecules is one of the most popular ones. Given the big number of lncRNAs, it becomes urgent and important to predict the RNA targets of lncRNAs in a large scale for the comprehensive understanding of lncRNA functions and action mechanisms. Although several methods have been developed to predict RNA-RNA interactions, none of them can be used to predict the RNA targets of lncRNAs in a large scale. Here we presented a tool, LncTar, which shows the ability to efficiently predict the RNA targets of lncRNAs in a large scale. To test the accuracy of LncTar, we applied it to 10 experimentally supported lncRNA-mRNA interactions. As a result, LncTar successfully predicted 8 (80%) of the 10 lncRNA-mRNA pairs, suggesting that LncTar has a reliable accuracy. Finally, we believe that LncTar could be an efficient tool for the fast identification of the RNA targets of lncRNAs. LncTar is freely available at http://www.cuilab.cn/lnctar.


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