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基因转录的随机模型:在L1逆转座事件中的应用。

A stochastic model of gene transcription: an application to L1 retrotransposition events.

作者信息

Rempala Grzegorz A, Ramos Kenneth S, Kalbfleisch Ted

机构信息

Department of Mathematics, University of Louisville, Louisville, KY 40292, USA.

出版信息

J Theor Biol. 2006 Sep 7;242(1):101-16. doi: 10.1016/j.jtbi.2006.02.010. Epub 2006 Apr 19.

Abstract

A simplified mathematical model of gene transcription is presented based on a system of coupled chemical reactions and a corresponding set of stochastic equations similar to those used in enzyme kinetics theory. The quasi-stationary distribution for the model is derived and its usefulness illustrated with an example of model parameters estimation using sparse time course data on L1 retrotransposon expression kinetics. The issue of model validation is also discussed and a simple validation procedure for the estimated model is devised. The procedure compares model predicted values with the laboratory data via the standard Bayesian techniques with the help of modern Markov-Chain Monte-Carlo methodology.

摘要

基于耦合化学反应系统和一组类似于酶动力学理论中使用的随机方程,提出了一种基因转录的简化数学模型。推导了该模型的准平稳分布,并通过使用关于L1逆转录转座子表达动力学的稀疏时间进程数据进行模型参数估计的示例来说明其有用性。还讨论了模型验证问题,并设计了一种针对估计模型的简单验证程序。该程序借助现代马尔可夫链蒙特卡罗方法,通过标准贝叶斯技术将模型预测值与实验室数据进行比较。

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