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MicroRNAs (miRNAs) are small non-coding RNAs that control gene expression atthe post-transcriptional level through complementary base pairing with thetarget mRNA, leading to mRNA degradation and blocking translation process. Anydysfunctions of these small regulatory molecules have been linked with thedevelopment and progression of several diseases. Therefore, it is necessary toreliably predict potential miRNA targets. A large number of computationalprediction tools have been developed which provide a faster way to findputative miRNA targets, but at the same time their results are ofteninconsistent. Hence, finding a reliable, functional miRNA target is still achallenging task. Also, each tool is equipped with different algorithms, and itis difficult for the biologists to know which tool is the best choice for theirstudy. This paper briefly describes fundamental of miRNA target predictionalgorithms, discuss frequently used prediction tools, and further, theperformance of frequently used prediction tools have been assessed usingexperimentally validated high confident mature miRNAs and their targets for twoorganisms Human and Drosophila Melanogaster. Both Drosophila Melanogaster andHuman supported miRNA target prediction tools have been evaluated separately tofind out best performing tool for each of these two organisms. In the humandataset, TargetScan showed the best results amongst the other predictorsfollowed by the miRmap and microT, whereas in the D. Melanogaster dataset,MicroT tool showed the best performance followed by the TargetScan in thecomparison of other tools.

Comprehensive overview and assessment of miRNA target prediction tools in human and drosophila melanogaster