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

TL;DR

This paper reviews miRNA target prediction tools, evaluates their performance on human and Drosophila datasets, and identifies the most reliable tools for each organism based on experimental validation.

Contribution

It provides a comprehensive comparison of prediction tools' performance on validated datasets for human and Drosophila melanogaster, guiding researchers in tool selection.

Findings

TargetScan performed best for human miRNA target prediction.

MicroT was the top performer for Drosophila melanogaster.

Different tools excel for different organisms.

Abstract

MicroRNAs (miRNAs) are small non-coding RNAs that control gene expression at the post-transcriptional level through complementary base pairing with the target mRNA, leading to mRNA degradation and blocking translation process. Any dysfunctions of these small regulatory molecules have been linked with the development and progression of several diseases. Therefore, it is necessary to reliably predict potential miRNA targets. A large number of computational prediction tools have been developed which provide a faster way to find putative miRNA targets, but at the same time their results are often inconsistent. Hence, finding a reliable, functional miRNA target is still a challenging task. Also, each tool is equipped with different algorithms, and it is difficult for the biologists to know which tool is the best choice for their study. This paper briefly describes fundamental of miRNA target prediction algorithms, discuss frequently used prediction tools, and further, the performance of frequently used prediction tools have been assessed using experimentally validated high confident mature miRNAs and their targets for two organisms Human and Drosophila Melanogaster. Both Drosophila Melanogaster and Human supported miRNA target prediction tools have been evaluated separately to find out best performing tool for each of these two organisms. In the human dataset, TargetScan showed the best results amongst the other predictors followed by the miRmap and microT, whereas in the D. Melanogaster dataset, MicroT tool showed the best performance followed by the TargetScan in the comparison of other tools.