MiRTif: a support vector machine-based microRNA target interaction filter

Abstract

Background: MicroRNAs (miRNAs) are a set of small non-coding RNAs serving as important negative gene regulators. In animals, miRNAs turn down protein translation by binding to the 3' UTR regions of target genes with imperfect complementary pairing. The identification of microRNA targets has become one of the major challenges of miRNA research. Bioinformatics investigations on miRNA target have resulted in a number of target prediction tools. Although these tools are capable of predicting hundreds of targets for a given miRNA, many of them suffer from high false positive rates, indicating the need for a post-processing filter for the predicted targets. Once trained with experimentally validated true and false targets, machine learning methods appear to be ideal approaches to distinguish the true targets from the false ones.

Regulation of WNK1 Expression by miR-192 and Aldosterone

“…If only miR-215-TS duplex was thus retrieved, central loop integration indicated that miR-192 was also able to target TS. 24 Finally, SVM postfitting of the predictions 25 revealed targeting of TS by miR-192 but not miR-215. This systematic computational exploration was a prompt method to further characterize this TS motif ( Table 1).…”

Computational Prediction of microRNAs and their Targets

“…Same algorithm, when used with data set collected from different sources, predictions are different. TargetScan with different data set of same species resulted only 47% overlap, whereas miRanda has given 65% overlap [75][76][77][78][79][80][81][82][83][84][85][86][87][88][89][90][91][92]. Researchers turned their attention to develop tools that employ multiple target finding programs, and obtain better result than what they could individually gained.…”

Predicting the target genes of microRNA based on microarray data

“…In the last few years, many computational methods and algorithms have been developed to predict miRNA targets, such as TargetScan, PicTar, miRanda, MirTif, and NBmiRTar (John et al, 2004;Krek et al, 2005;Yang et al, 2008;Garcia et al, 2011). Most of these methods or algorithms were based on the following criteria: 1) strong Watson-Crick base-pairing of the 5ꞌ seed of the miRNA to a complementary site in the 3ꞌ-UTR of the mRNA, 2) conservation of the miRNA binding site, and 3) a local miRNA-mRNA interaction with a positive balance of minimum free energy (Barbato et al, 2009).…”