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首页> 外文期刊>Chaos, Solitons and Fractals: Applications in Science and Engineering: An Interdisciplinary Journal of Nonlinear Science >Stochastic resonance in a genetic toggle model with harmonic excitation and Levy noise
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Stochastic resonance in a genetic toggle model with harmonic excitation and Levy noise

机译:具有谐波激励和利维噪声的遗传翻转模型中的随机共振

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摘要

Stochastic resonance is investigated to explain the beneficial effect of Levy noise on gene expression of genetic toggle model with harmonic excitation. The dynamic change of protein concentration of genetic toggle model under combined drives of harmonic excitation and Levy noise is obtained numerically. Stochastic resonance is presented through the classical measure of signal-to-noise-ratio. Then from two aspects of combined drives on the protein at high or low concentration, the changes of protein concentration and signal-to-noise-ratio are discussed, respectively. When combined drives are within the protein at high concentration, the increasing Levy noise intensity can promote the transition between the high and low concentrations, and the low protein concentration hardly fluctuates under the small noise intensity. It is also shown that the increase of stability index, skewness parameter of Levy noise and amplitude of harmonic excitation can suppress the optimum collaboration of stochastic resonance. On the other hand, when combined drives are within the protein at low concentration, the increasing noise intensity can enhance the transition between the high and low concentrations, and the increase of stability index, skewness parameter and amplitude can strengthen the optimum collaboration of stochastic resonance. By the synergic actions of stochastic resonance, it is demonstrated that combined effect of harmonic excitation and Levy stimuli can be utilized to promote the gene expression of proteins in genetic toggle model. (C) 2016 Elsevier Ltd. All rights reserved.
机译:研究了随机共振以解释征费对谐波激发的遗传触发模型的基因表达的有益影响。数值计算了在谐波激励和利维噪声联合驱动下遗传切换模型蛋白质浓度的动态变化。随机共振是通过经典的信噪比度量来表示的。然后从高浓度或低浓度对蛋白质的联合驱动两个方面,分别讨论了蛋白质浓度和信噪比的变化。当组合驱动器处于高浓度蛋白质中时,不断增加的Levy噪声强度可以促进高浓度和低浓度之间的转换,而低蛋白质浓度在低噪声强度下几乎不会波动。研究还表明,稳定指数,Levy噪声偏度参数和谐波激励幅度的增加可以抑制随机共振的最佳配合。另一方面,当组合驱动器处于低浓度的蛋白质中时,增加的噪声强度可以增强高浓度和低浓度之间的过渡,并且稳定性指数,偏度参数和振幅的增加可以增强随机共振的最佳协作。 。通过随机共振的协同作用,证明了谐波激发和利维刺激的联合作用可用于促进遗传触发模型中蛋白质的基因表达。 (C)2016 Elsevier Ltd.保留所有权利。

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