Advances and Applications in Statistics
Volume 53, Issue 6, Pages 693 - 713
(December 2018) http://dx.doi.org/10.17654/AS053060693 |
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A STATISTICAL APPROACH FOR UNDERSTANDING THE PLETHORA OF miRNAS AND mRNAS INTERPLAY
Medhat M. Abdel Aal, Mamdouh A. Alim Saad Mowafy and Nehal Etman
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Abstract: Gene expression regulation is a vital process in the body to ensure that cells produce the correct amount of proteins when they need them. Any disruption to this regulation can lead to serious consequences, including cancer. Regulation of gene expression includes a wide range of mechanisms that are used by cells to increase or decrease the production of specific gene products. miRNAs are micro molecules that control gene expression by targeting an mRNA and binding to specific sites within the 3'UTR or the 5'UTR and increase or decrease gene expression. The mechanisms by which miRNAs act are not fully understood. The first step toward unraveling the function of a particular miRNA is the identification of its direct targets. Several methods are now available for identifying miRNA target sites, from the modeling of physical interactions to the incorporation of machine learning but the mere presence of a miRNA-binding site is insufficient for predicting target regulation. Up to now, the most studied model in miRNAs is a transcriptional repression (degradation) of mRNA levels and translation. Recent studies have outlined that miRNAs area able not only to repress, but also activate, gene expression, acting on mRNA stability and translation regulation. In this review, we attempt to understand interactions between miRNAs and their targets, the increase or decrease of gene expression when miRNAs bind to specific sites within the 3ï‚¢UTR of an mRNA. In this sense we propose new computational approaches to predict the positive or negative effect of the miRNAs on the regulation of gene expression. |
Keywords and phrases: gene expression regulation, microRNA, mRNA, seed match, free energy, logistic regression.
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