Simulating Evolution of Drosophila Melanogaster Ebony Mutants Using a Genetic Algorithm

Genetic algorithms are generally quite easy to understand and work with, and they are a popular choice in many cases. One area in which genetic algorithms are widely and successfully used is artificial life where they are used to simulate evolution of artificial creatures. However, despite their suggestive name, simplicity and popularity in artificial life, they do not seem to have gained a footing within the field of population genetics to simulate evolution of real organisms - possibly because genetic algorithms are based on a rather crude simplification of the evolutionary mechanisms known today. However, in this paper we report how a standard genetic algorithm is used to successfully simulate evolution of ebony mutants in a population of Drosophila melanogaster (D.melanogaster). The results show a remarkable resemblance to the evolution observed in real biological experiments with ebony mutants, indicating that despite the simplifications, even a simple standard genetic algorithm does indeed capture the governing principles in evolution, and could be used beneficially in population genetics studies.