arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1409.3499q-bio.MNcond-mat.stat-mechphysics.bio-ph
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具有反馈和突发的随机基因表达模型的精确分布

Exact distributions for stochastic gene expression models with bursting and feedback

Niraj Kumar, Thierry Platini, Rahul V. Kulkarni

摘要:

基因表达的随机性可引起蛋白质水平的波动,并导致遗传相同细胞群体中的表型变异。最近的实验表明,爆发和反馈机制在控制基因表达和表型变异的噪声中起着重要作用。定量了解这些因素的影响,需要分析相应的随机模型。然而,对于具有反馈和突发的基因表达随机模型,迄今为止还没有得到蛋白质分布的精确分析结果。在这里,我们分析了一个具有突发和反馈调节的基因表达模型,并得到了相应的蛋白质稳态分布的精确结果。所获得的结果提供了新的见解突发和反馈的作用,在噪声调节和优化。此外,对于一个特定的参数选择,系统研究映射到一个双态生化开关驱动的突发输入噪声源。因此,衍生的分析结果提供了定量的见解,涉及噪音在基因表达和生化开关不同的细胞过程。

英文摘要:

Stochasticity in gene expression can give rise to fluctuations in protein levels and lead to phenotypic variation across a population of genetically identical cells. Recent experiments indicate that bursting and feedback mechanisms play important roles in controlling noise in gene expression and phenotypic variation. A quantitative understanding of the impact of these factors requires analysis of the corresponding stochastic models. However, for stochastic models of gene expression with feedback and bursting, exact analytical results for protein distributions have not been obtained so far. Here, we analyze a model of gene expression with bursting and feedback regulation and obtain exact results for the corresponding protein steady-state distribution. The results obtained provide new insights into the role of bursting and feedback in noise regulation and optimization. Furthermore, for a specific choice of parameters, the system studied maps on to a two-state biochemical switch driven by a bursty input noise source. The analytical results derived thus provide quantitative insights into diverse cellular processes involving noise in gene expression and biochemical switching.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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