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鲁里亚-德尔布吕克分布的显式表示。

An explicit representation of the Luria-Delbrück distribution.

作者信息

Angerer W P

机构信息

Department of Molecular Genetics, Institute of Cancer Research, Borschkegasse 8a, A-1090 Vienna, Austria.

出版信息

J Math Biol. 2001 Feb;42(2):145-74. doi: 10.1007/s002850000053.

DOI:10.1007/s002850000053
PMID:11261316
Abstract

The probability distribution of the number of mutant cells in a growing single-cell population is presented in explicit form. We use a discrete model for mutation and population growth which in the limit of large cell numbers and small mutation rates reduces to certain classical models of the Luria-Delbrück distribution. Our results hold for arbitrarily large values of the mutation rate and for cell populations of arbitrary size. We discuss the influence of cell death on fluctuation experiments and investigate a version of our model that accounts for the possibility that both daughter cells of a non-mutant cell might be mutants. An algorithm is presented for the quick calculation of the distribution. Then, we focus on the derivation of two essentially different limit laws, the first of which applies if the population size tends to infinity while the mutation rate tends to zero such that the product of mutation rate times population size converges. The second limit law emerges after a suitable rescaling of the distribution of non-mutant cells in the population and applies if the product of mutation rate times population size tends to infinity. We discuss the distribution of mutation events for arbitrary values of the mutation rate and cell populations of arbitrary size, and, finally, consider limit laws for this distribution with respect to the behavior of the product of mutation rate times population size. Thus, the present paper substantially extends results due to Lea and Coulson (1949), Bartlett (1955), Stewart et al. (1990), and others.

摘要

给出了生长中的单细胞群体中突变细胞数量的概率分布的显式形式。我们使用一个用于突变和群体生长的离散模型,在细胞数量大且突变率小的极限情况下,该模型简化为某些经典的卢里亚 - 德尔布吕克分布模型。我们的结果适用于任意大的突变率值和任意大小的细胞群体。我们讨论了细胞死亡对波动实验的影响,并研究了我们模型的一个版本,该版本考虑了非突变细胞的两个子细胞都可能是突变体的可能性。提出了一种用于快速计算分布的算法。然后,我们专注于推导两个本质上不同的极限定律,第一个适用于群体大小趋于无穷大而突变率趋于零,使得突变率乘以群体大小的乘积收敛的情况。第二个极限定律是在对群体中非突变细胞的分布进行适当的重新标度后出现的,并且适用于突变率乘以群体大小的乘积趋于无穷大的情况。我们讨论了任意突变率值和任意大小的细胞群体的突变事件分布,最后考虑了关于突变率乘以群体大小的乘积的行为的该分布的极限定律。因此,本文大大扩展了利和库尔森(1949 年)、巴特利特(1955 年)、斯图尔特等人(1990 年)及其他学者的结果。

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