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精确马尔可夫链与扩散理论在单体随机交配中的比较。

Exact Markov chains versus diffusion theory for haploid random mating.

机构信息

Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, P.O. Box 5003, 1432 As, Norway.

出版信息

Math Biosci. 2010 May;225(1):18-23. doi: 10.1016/j.mbs.2010.01.005. Epub 2010 Jan 25.

Abstract

Exact discrete Markov chains are applied to the Wright-Fisher model and the Moran model of haploid random mating. Selection and mutations are neglected. At each discrete value of time t there is a given number n of diploid monoecious organisms. The evolution of the population distribution is given in diffusion variables, to compare the two models of random mating with their common diffusion limit. Only the Moran model converges uniformly to the diffusion limit near the boundary. The Wright-Fisher model allows the population size to change with the generations. Diffusion theory tends to under-predict the loss of genetic information when a population enters a bottleneck.

摘要

确切的离散马尔可夫链被应用于 Wright-Fisher 模型和单体随机交配的 Moran 模型。选择和突变被忽略。在每个离散的时间 t 值处,有给定数量 n 的二倍体雌雄同体生物。种群分布的演化以扩散变量给出,以比较两种随机交配模型及其共同的扩散极限。只有 Moran 模型在边界附近一致地收敛到扩散极限。Wright-Fisher 模型允许种群大小随世代变化。当种群进入瓶颈时,扩散理论倾向于低估遗传信息的损失。

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