Dynamics of genetic code evolution: The emergence of universality
We study the dynamics of genetic code evolution. The model of Vetsigian et al. [1] and Vetsigian [2] uses the mechanism of horizontal gene transfer to demonstrate convergence of the genetic code to a near universal solution. We reproduce and analyze the algorithm as a dynamical system. All the parameters used in the model are varied to assess their impact on convergence and optimality score. We show that by allowing specific parameters to vary with time, the solution exhibits attractor dynamics. 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 re-examine universality and find that there is a direct link to mutation rate.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Emergence-focused design in complex system simulation
Emergence is a phenomenon taken for granted in science but also still not well understood. We have developed a model of artificial genetic evolution intended to allow for emergence on genetic, population and social level…
Emergence of more contagious COVID-19 variants from the coevolution of viruses and policy interventions
At the end of 2020, policy responses to the SARS-CoV-2 outbreak have been shaken by the emergence of virus variants. The emergence of these more contagious, more severe, or even vaccine-resistant strains have challenged …
Simple model for the Darwinian transition in early evolution
It has been hypothesized that in the era just before the last universal common ancestor emerged, life on earth was fundamentally collective. Ancient life forms shared their genetic material freely through massive horizon…
Extended Inclusive Fitness Theory bridges Economics and Biology through a common understanding of Social Synergy
Inclusive Fitness Theory (IFT) was proposed half a century ago by W.D. Hamilton to explain the emergence and maintenance of cooperation between individuals that allows the existence of society. Contemporary evolutionary …
How Information Evolves: Stability-Driven Assembly and the Emergence of a Natural Genetic Algorithm
Information can evolve as a physical consequence of non-equilibrium dynamics, even in the absence of genes, replication, or predefined fitness functions. We present Stability-Driven Assembly (SDA), a framework in which s…