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Cardiovascular diseases (CVDs) are globally the number 1 cause of death. Despite improvement in treatment strategies, heart disorders are strongly increasing. Therefore, identification of new regulatory factors involved in the cardiac differentiation is very important. TRKC receptor, part of the large family of receptor tyrosine kinases, is involved in development of the heart and central nervous system. There are many contradictory functions related to the TRKC gene which might be attributed to the non-coding RNAs located in it. Recently, a novel miRNA, hsa-miR-11181-5p located in TRKC gene, has been reported which is involved in nervous differentiation. MiRNAs are small non-coding RNAs regulating their target genes via mRNA degradation or protein inhibition. The goal of the present study was to investigate the expression pattern of hsa-miR-11181-5p during the course of cardiosphere-derived cells (CDCs) differentiation.

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Although more than 98% of the human genome is transcribed, most of these transcripts are not translated into proteins. Rather, they are considered as non-coding RNAs. MicroRNAs (miRNAs) are very short non-coding RNAs approximately 22 nucleotides in length which regulate many key processes of cells such as growth, proliferation, differentiation, cell cycle, apoptosis (programmed cell death) and metabolism. On the other hand, it is known that these small regulatory molecules are involved in many human diseases such as different cancers and cardiovascular disorders. Therefore, discovery and functional characterization of novel miRNAs is a prominent achievement. Low abundance and spatiotemporal expression of these mediator molecules make their discovery difficult by conventional methods. Therefore, bioinformatics software have been designed for the prediction of stem-loop structures capable of producing miRNA precursors in the human genome. On the other hand, there are several bioinformatics tools for prediction of miRNA target genes. Prediction of miRNA target genes helps to characterize the function of a miRNA. In this paper, we have reviewed some of the common efficient bioinformatics tools and experimental approaches used for prediction and identification of the miRNA genes and their target genes.