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Observation and control in models of population genetics

机译:人口遗传学模型中的观察与控制

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Mathematical systems theory and optimal control have been mostly developed in the context of engineering. In this paper it is shown how these techniques can be applied in population genetics. Based on the classical Fisher's selection model, first a very natural monitoring problem is studied: can the change of the genetic state of a population (described in terms of allele frequencies) be uniquely recovered from the observation of the frequencies of certain phenotypes? We give sufficient conditions for a positive answer to this question in a typical case of heterosis (when mixed genotypes are better than the pure ones, implying stable coexistence of all allele types). The second question is: How to effectively estimate the genetic composition of the population from phenotypic observation? The answer is observer design, which is carried out for two different dominance structures, determining the manifestation of the genetic state. In a model of artificial selection, we show how the population can be steered into equilibrium where maximal mean fitness is attained. Finally, the application of the above methodology is also extended to selection-mutation models, where both fitness parameters and mutation rates are controlled. (C) 2017 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
机译:数学系统理论和最优控制主要是在工程领域内发展起来的。本文显示了如何将这些技术应用于群体遗传学。首先,基于经典的费舍尔选择模型,研究一个非常自然的监测问题:是否可以通过观察某些表型的频率来唯一地恢复种群遗传状态的变化(以等位基因频率表示)?在杂种优势的典型情况下(当混合基因型比纯基因型更好时,这意味着所有等位基因类型都稳定存在),我们为充分回答该问题提供了充分的条件。第二个问题是:如何从表型观察中有效估计种群的遗传组成?答案是观察者设计,它是针对两个不同的优势结构进行的,确定了遗传状态的表现形式。在人工选择的模型中,我们展示了如何在达到最大平均适应度的情况下将种群转向均衡。最后,上述方法的应用也扩展到选择突变模型,其中适应性参数和突变率均受到控制。 (C)2017富兰克林研究所。由Elsevier Ltd.出版。保留所有权利。

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  • 来源
    《Journal of the Franklin Institute》 |2017年第16期|7359-7384|共26页
  • 作者单位

    Univ Almeria, Dept Math, La Canada De San Urbano 04120, Almeria, Spain;

    Univ Almeria, Dept Math, La Canada De San Urbano 04120, Almeria, Spain;

    Univ Almeria, Dept Math, La Canada De San Urbano 04120, Almeria, Spain;

    Szent Istvan Univ, Inst Math & Informat, Pater K U 1, H-2103 Godollo, Hungary;

    Eotvos Lorand Univ, MTA ELTE Theoret Biol & Evolutionary Ecol Res Grp, Pazmany P Setany 1-C, H-1117 Budapest, Hungary|Eotvos Lorand Univ, Dept Plant Systemat Ecol & Theoret Biol, Pazmany P Setany 1-C, H-1117 Budapest, Hungary;

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  • 入库时间 2022-08-18 02:57:45

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