An evolutionary model with Turing machines

TL;DR

This paper presents a computational model demonstrating that maintaining a large non-coding DNA fraction can provide long-term evolutionary advantages, inspired by biological and computational phenomena.

Contribution

It introduces an evolutionary model with Turing machines showing the benefits of non-coding regions for evolution, a novel approach linking biology and computation.

Findings

Large non-coding fractions confer evolutionary benefits

Code growth mechanisms influence coding/non-coding ratios

Simulation results support the advantage of non-coding reservoirs

Abstract

The development of a large non-coding fraction in eukaryotic DNA and the phenomenon of the code-bloat in the field of evolutionary computations show a striking similarity. This seems to suggest that (in the presence of mechanisms of code growth) the evolution of a complex code can't be attained without maintaining a large inactive fraction. To test this hypothesis we performed computer simulations of an evolutionary toy model for Turing machines, studying the relations among fitness and coding/non-coding ratio while varying mutation and code growth rates. The results suggest that, in our model, having a large reservoir of non-coding states constitutes a great (long term) evolutionary advantage.