Soft Computing Model for Optimized siRNA Design by identifying Off Target possibilities using Artificial Neural Network Model.

Soft Computing Model for Optimized siRNA Design by identifying Off Target possibilities using Artificial Neural Network Model. Gene. 2015 Feb 25; Authors: Murali R, John PG, S DP Abstract The ability of small interfering RNA (siRNA) to do post transcriptional gene regulation by knocking down targeted genes is an important research topic in functional genomics, biomedical research and in cancer therapeutics. Many tools had been developed to design exogenous siRNA with high experimental inhibition. Even though considerable amount of work has been done in designing exogenous siRNA, design of effective siRNA sequences is still a challenging work because the target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. In some cases, siRNAs may tolerate mismatches with the target mRNA, but knockdown of genes other than the intended target could make serious consequences. Hence to design siRNAs, two important concepts must be considered: the ability in knocking down target genes and the off target possibility on any non target genes. So before doing gene silencing by siRNAs, it is essential to analyze their off target effects in addition to their inhibition efficacy against a particular target. Only a few methods have been developed by considering both efficacy and off target possibility of siRNA against a ...
Source: Gene - Category: Genetics & Stem Cells Authors: Tags: Gene Source Type: research