Bio Inspired Computing Model For Gene Editing Using Insertion Deletion Systems

Abstract

Bio inspired computing system is playing a vital in providing solutions to complex problems using biological processes. They find wide applications in designing intelligent systems and optimization problems. In this research, four bio inspired computing models for editing genes using insertion deletion systems has been designed, implemented and tested. The first system uses indexed grammar based editing system for identifying malformations in the gene and correcting them using the insertion deletion system based on indexed grammar. The second system employs a matrix based insertion deletion system for gene editing. The regions to be edited are identified using molecular sequence weight measure. The third system uses RNA sequence support measure to identify regions to be edited. Based on the deviations in the identified region, insertion deletion operations are performed using a matrix insertion deletion system. The fourth system uses template match measure for malformed regions in the input gene expression. The faulty genes are corrected using matrix insertion deletion systems in real time. All the four proposed systems exhibited good performance when experimented with the GEO datasets. The systems clearly outperformed earlier systems in terms of accuracy, false classification rate, time complexity and risk detection rate. Out of the four proposed systems, the real time RNA editing system using template match measure outperformed the others. newline