  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.
