Exploration of RNA Editing and Design of Robust Genetic Algorithms

TL;DR

This paper explores RNA editing's role in enhancing genetic algorithms' robustness by integrating artificial editing mechanisms, providing insights into evolution and practical applications.

Contribution

It introduces a novel framework combining RNA editing characteristics with genetic algorithms to improve their adaptability and robustness.

Findings

RNA editing mechanisms increase phenotypic plasticity in GAs

Enhanced GAs show promising results on real-world problems

Framework aids understanding of RNA editing's evolutionary role

Abstract

This paper presents our computational methodology using Genetic Algorithms (GA) for exploring the nature of RNA editing. These models are constructed using several genetic editing characteristics that are gleaned from the RNA editing system as observed in several organisms. We have expanded the traditional Genetic Algorithm with artificial editing mechanisms as proposed by (Rocha, 1997). The incorporation of editing mechanisms provides a means for artificial agents with genetic descriptions to gain greater phenotypic plasticity, which may be environmentally regulated. Our first implementations of these ideas have shed some light into the evolutionary implications of RNA editing. Based on these understandings, we demonstrate how to select proper RNA editors for designing more robust GAs, and the results will show promising applications to real-world problems. We expect that the framework proposed will both facilitate determining the evolutionary role of RNA editing in biology, and advance the current state of research in Genetic Algorithms.