Dynamics of genetic code evolution: The emergence of universality
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.
Argyriadis John-Antonio、He Yang-Hui、Minic Djordje、Jejjala Vishnu
Jesus College, University of Oxford Rudolf Peierls Centre for Theoretical Physics, Clarendon Laboratory, Parks Rd, University of OxfordDepartment of Mathematics, City, University of London Merton College, University of Oxford School of Physics, NanKai UniversityDepartment of Physics, Virginia TechMandelstam Institute for Theoretical Physics, School of Physics, NITheP, and CoE-MaSS, University of the Witwatersrand, Johannesburg David Rittenhouse Laboratory, University of Pennsylvania
遗传学生物科学理论、生物科学方法生物科学研究方法、生物科学研究技术
Argyriadis John-Antonio,He Yang-Hui,Minic Djordje,Jejjala Vishnu.Dynamics of genetic code evolution: The emergence of universality[EB/OL].(2025-03-28)[2025-05-07].https://www.biorxiv.org/content/10.1101/779959.点此复制
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