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1- Department of Biological Science, Faculty of Science, University of Kurdistan, Sanandaj, Iran
2- Department of Biological Science, Faculty of Science, University of Kurdistan, Sanandaj, Iran, Department of Biological Science, Faculty of Science, University of Kurdistan, Sanandaj, Iran , sh.ahmadi@uok.ac.ir
Abstract:   (473 Views)
MicroRNAs are a group of small non-coding RNAs that regulate gene expression in eukaryotes at the post-transcriptional level. MicroRNAs, through regulating the expression of large numbers of mRNAs, act as major regulators of various biological processes such as embryonic development, cell proliferation, differentiation, and apoptosis. Therefore, the identification of microRNAs and their target genes is very effective in finding the mechanisms of embryonic development, growth, and also the processes underlying the induction and progression of various diseases. Because of the high costs of molecular experiments, the identification of effective microRNAs through bioinformatics tools and computational biology is faster and cheaper than the experimental methods. Several online bioinformatics tools and databases have been developed and are freely available for predicting microRNAs target genes. The available online tools use a broad range of information, including sequencing data, gene expression data, and computational algorithms for predicting microRNAs target genes. Some of the most important of these online tolls are miRWalk, TargetScan, RNAhybrid, Diana-microT, miRanda, and MirTarget. The four main features of the interaction between a microRNA and an mRNA, including seed pairing, sequence conservation, free energy, and access to the binding site in a target are used in the algorithm of all of these prediction tools. This stud aimed to review the latest findings on the characteristics and capabilities of microRNA target prediction tools, comparing the performance of these tools, and finally introducing the most efficient tool in the field of target gene prediction for bioinformatics, biomedicine, and molecular medicine studies.
     
Article Type: Analytic Review | Subject: Bioinformatics
Received: 2021/01/11 | Accepted: 2021/09/11

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