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Relaxation rates of gene expression kinetics reveal the feedback signs of autoregulatory gene networks

机译:基因表达动力学的放松率揭示了自身化基因网络的反馈迹象

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The transient response to a stimulus and subsequent recovery to a steady state are the fundamental characteristics of a living organism. Here we study the relaxation kinetics of autoregulatory gene networks based on the chemical master equation model of single-cell stochastic gene expression with nonlinear feedback regulation. We report a novel relation between the rate of relaxation, characterized by the spectral gap of the Markov model, and the feedback sign of the underlying gene circuit. When a network has no feedback, the relaxation rate is exactly the decaying rate of the protein. We further show that positive feedback always slows down the relaxation kinetics while negative feedback always speeds it up. Numerical simulations demonstrate that this relation provides a possible method to infer the feedback topology of autoregulatory gene networks by using time-series data of gene expression. Published by AIP Publishing.
机译:对刺激的瞬态响应和随后恢复到稳定状态是生物体的基本特征。 在这里,我们基于非线性反馈调节的单细胞随机基因表达的化学母体方程模型研究自身调节基因网络的弛豫动力学。 我们在放松率之间报告了一种新的关系,其特征在于Markov模型的光谱间隙,以及底层基因电路的反馈符号。 当网络没有反馈时,弛豫率正好是蛋白质的腐烂率。 我们进一步表明,积极的反馈总是减慢放松动力学,而负面反馈总是加速。 数值模拟表明,该关系提供了通过使用基因表达的时间序列数据来推断自动调节基因网络的反馈拓扑的方法。 通过AIP发布发布。

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