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首页> 外文期刊>Mathematical Biosciences: An International Journal >Stochastic and delayed stochastic models of gene expression and regulation
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Stochastic and delayed stochastic models of gene expression and regulation

机译：基因表达和调控的随机和延迟随机模型

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摘要

Gene expression and gene regulatory networks dynamics are stochastic. The noise in the temporal amounts of proteins and RNA molecules in cells arises from the stochasticity, of transcription initiation and elongation (e.g., due to RNA polymerase pausing), translation, and post-transcriptional regulation mechanisms, such as reversible phosphorylation and splicing. This is further enhanced by the fact that most RNA molecules and proteins exist in cells in very small amounts. Recently, the time needed for transcription and translation to be completed once initiated were shown to affect the stochasticity in gene networks. This observation stressed the need of either introducing explicit delays in models of transcription and translation or to model processes such as elongation at the single nucleotide level. Here we review stochastic and delayed stochastic models of gene expression and gene regulatory networks. We first present stochastic non-delayed and delayed models of transcription, followed by models at the single nuclecitide level. Next, we present models of gene regulatory networks, describe the dynamics of specific stochastic gene networks and available simulators to implement these models.
机译：基因表达和基因调控网络的动力学是随机的。细胞中蛋白质和RNA分子在时间上的噪声来自于随机性，转录起始和延伸（例如由于RNA聚合酶暂停），翻译和转录后调控机制（例如可逆的磷酸化和剪接）。大多数RNA分子和蛋白质以非常少量存在于细胞中的事实进一步增强了这一点。最近，转录和翻译一旦启动就需要完成的时间显示出会影响基因网络的随机性。该观察结果强调了需要在转录和翻译模型中引入显式延迟，或者对诸如单核苷酸水平的延伸进行建模的过程。在这里，我们回顾了基因表达和基因调控网络的随机和延迟随机模型。我们首先介绍随机的非延迟和延迟转录模型，然后是单核苷酸水平的模型。接下来，我们介绍基因调控网络的模型，描述特定随机基因网络的动力学以及可用于实现这些模型的模拟器。

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