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arXiv 0704.2793q-bio.MNq-bio.QM
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随机遗传电路的确定性特征

Deterministic characterization of stochastic genetic circuits

Matthew Scott, Terence Hwa, Brian Ingalls

摘要:

对于其中分子数目小的细胞生物化学反应系统,显著的噪声与化学反应事件相关联。这种分子噪声可以引起与确定性速率方程模型的预测非常不同的行为。不幸的是,很少有分析方法来检查随机系统的定性行为。在这里,我们描述了这样一种方法,扩展确定性分析,包括由于分子噪声的领先阶校正。该方法允许的随机模型的稳态行为,易于计算,有利于映射的稳定性相图,包括随机效应,并揭示了模型参数如何影响噪声敏感性,在某种程度上无法访问的数值模拟。作为说明,我们考虑两个遗传电路:一个正反馈回路和一个负反馈振荡器。我们发现,在正反馈回路中,翻译激活导致一个比转录控制更稳定的系统。相反,在由正反馈开关触发的负反馈回路中,转录控制的随机性被利用来产生可再现的振荡。

英文摘要:

For cellular biochemical reaction systems where the numbers of molecules is small, significant noise is associated with chemical reaction events. This molecular noise can give rise to behavior that is very different from the predictions of deterministic rate equation models. Unfortunately, there are few analytic methods for examining the qualitative behavior of stochastic systems. Here we describe such a method that extends deterministic analysis to include leading-order corrections due to the molecular noise. The method allows the steady-state behavior of the stochastic model to be easily computed, facilitates the mapping of stability phase diagrams that include stochastic effects and reveals how model parameters affect noise susceptibility, in a manner not accessible to numerical simulation. By way of illustration we consider two genetic circuits: a bistable positive-feedback loop and a negative-feedback oscillator. We find in the positive feedback circuit that translational activation leads to a far more stable system than transcriptional control. Conversely, in a negative-feedback loop triggered by a positive-feedback switch, the stochasticity of transcriptional control is harnessed to generate reproducible oscillations.

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