Browsing by Author "Park, Jeong-Man"

Now showing 1 - 3 of 3
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    Evolutionary processes in finite populations
    (American Physical Society, 2013) Lorenz, Dirk M.; Park, Jeong-Man; Deem, Michael W.
    We consider the evolution of large but finite populations on arbitrary fitness landscapes. We describe the evolutionary process by a Markov-Moran process.We show that toO(1/N), the time-averaged fitness is lower for the finite population than it is for the infinite population.We also showthat fluctuations in the number of individuals for a given genotype can be proportional to a power of the inverse of the mutation rate. Finally, we show that the probability for the system to take a given path through the fitness landscape can be nonmonotonic in system size.
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    Modularity enhances the rate of evolution in a rugged fitness landscape
    (IOP Publishing Ltd, 2015) Park, Jeong-Man; Chen, Man; Wang, Dong; Deem, Michael W.; Center for Theoretical Biological Physics
    Biological systems are modular, and this modularity affects the evolution of biological systems over time and in different environments. We here develop a theory for the dynamics of evolution in a rugged, modular fitness landscape. We show analytically how horizontal gene transfer couples to the modularity in the system and leads to more rapid rates of evolution at short times. The model, in general, analytically demonstrates a selective pressure for the prevalence of modularity in biology. We use this model to show how the evolution of the influenza virus is affected by the modularity of the proteins that are recognized by the human immune system. Approximately 25% of the observed rate of fitness increase of the virus could be ascribed to a modular viral landscape.
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    Quasispecies theory for evolution of modularity
    (American Physical Society, 2015) Park, Jeong-Man; Niestemski, Liang Ren; Deem, Michael W.
    Biological systems are modular, and this modularity evolves over time and in different environments. A number of observations have been made of increased modularity in biological systems under increased environmental pressure. We here develop a quasispecies theory for the dynamics of modularity in populations of these systems. We show how the steady-state fitness in a randomly changing environment can be computed. We derive a fluctuation dissipation relation for the rate of change of modularity and use it to derive a relationship between rate of environmental changes and rate of growth of modularity. We also find a principle of least action for the evolved modularity at steady state. Finally, we compare our predictions to simulations of protein evolution and find them to be consistent.