Selection under random mutations in stochastic Eigen model

Inagaki, H.

doi:10.1016/s0092-8240(82)80028-1

Cited by 5 publications

(1 citation statement)

References 13 publications

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“…The stochastic versions of the Eigen model were built by physical methods, such as the Langevin equation and Markov process. The stochastic dynamics of species evolution were elucidated in these random models (Galstyan and Saakian, 2012;Inagaki, 1982). Nevertheless, the stochastic characteristics on the Eigen model have not been well understood.…”

Section: ． Introductionmentioning

confidence: 99%

Statistical properties and error threshold of quasispecies on single-peak Gaussian-distributed fitness landscapes

Cao

Geng

et al. 2015

Journal of Theoretical Biology

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The stochastic Eigen model proposed by Feng et al. (2007) (Journal of Theoretical Biology, 246, 28) showed that error threshold is no longer a phase transition point but a crossover region whose width depends on the strength of the random fluctuation in an environment. The underlying cause of this phenomenon has not yet been well examined. In this article, we adopt a single peak Gaussian distributed fitness landscape instead of a constant one to investigate and analyze the change of the error threshold and the statistical property of the quasi-species population. We find a roughly linear relation between the width of the error threshold and the fitness fluctuation strength. For a given quasi-species, the fluctuation of the relative concentration has a minimum with a normal distribution of the relative concentration at the maximum of the averaged relative concentration, it has however a largest value with a bimodal distribution of the relative concentration near the error threshold. The above results deepen our understanding of the quasispecies and error threshold and are heuristic for exploring practicable antiviral strategies.

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Section: ． Introductionmentioning

confidence: 99%