Dynamics of genetic code evolution: The emergence of universality

Abstract

We study the dynamics of genetic code evolution. The algorithm of Vetsigian et al.[1] provides a solution that is both optimal and universal. We reproduce and analyze the algorithm as a dynamical system. All the parameters used in the model are varied to assess their impact on achieving universality. We show that by allowing specific parameters to vary with time, the algorithm converges much faster to a universal solution. Finally, we study automorphisms of the genetic code arising due to this model. We use this to examine the scaling of the solutions in order to understand the origin of universality and find that there is a direct link to mutation rate.

Quantum Gravity and Phenomenology: Dark Matter, Dark Energy, Vacuum Selection, Emergent Spacetime, and Wormholes

“…We are interested in applying these ideas in the context of string theory, where the horizontal transfer of information between different perturbative string vacua is modeled by string interactions. It turns out that the topological string information about compactifications can be mapped into biological data and the same mechanism for the universal vacuum selection found in biophysics may be applied in string theory [53]. This work also nicely relates to the current efforts to apply the techniques from machine learning and AI in the study of string vacua [54][55][56].…”