2008/02/27 by Kavita Jain
Biochemistry, Genetics and Molecular Biology · Medicine · Physics and Astronomy · Social Sciences · #Adaptation (eye) #Artificial intelligence #Biology #Computer science #Demography #Evolution and Genetic Dynamics #Evolutionary Game Theory and Cooperation #Evolutionary biology #Evolutionary dynamics #Fitness landscape #Genetic Fitness #Genetics #Mathematical and Theoretical Epidemiology and Ecology Models #Mutation #Mutation rate #Physics #Population #Selection (genetic algorithm) #Statistical physics #Survival of the fittest #Viral quasispecies #cond-mat.stat-mech #q-bio.PE
paper · pdf · doi:10.1007/s12043-008-0160-7
published as Pramana- J. Phys. 71, 275 (2008) · Proceedings of Statphys conference at IIT Guwahati, to be published in Pramana
arxiv created 2008/02/27 · openalex publication_date 2008/08/01 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen's model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a \it quasispecies which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.