Muniba Faiza, Khushnuma Tanveer, Saman Fatihi, Yonghua Wang and Khalid Raza*
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. Many dysfunctions of these small regulatory molecules have been linked to 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 miRNA target prediction algorithms, discusses common features of frequently used target prediction tools, and further, the performance of these prediction tools have been assessed using experimentally validated high confident mature miRNAs and their targets for two organisms Homo sapiens and Drosophila melanogaster. Both Drosophila melanogaster and Homo sapiens supported miRNA target prediction tools have been evaluated separately to find out best-performing tool for each of these two organisms.
microRNA target prediction, target prediction algorithm, transcript prediction, feature extraction
School of Food Science and Engineering, South China University of Technology, Guangzhou, Department of Computer Science, Jamia Millia Islamia, New Delhi-110025, Department of Computer Science, Jamia Millia Islamia, New Delhi-110025, School of Food Science and Engineering, South China University of Technology, Guangzhou, Department of Computer Science, Jamia Millia Islamia, New Delhi-110025