具有共同激发子的退化-着火振子群中簇周期轨道稳定性的反馈-延迟依赖。

IF 2.3 4区 数学 Q2 BIOLOGY
Bastien Fernandez, Matteo Tanzi
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引用次数: 0

摘要

反馈延迟已被确定为合成基因振荡器群体感应同步的关键因素。虽然这种影响已经在理论水平上通过一个共同的激活蛋白耦合的退化-燃烧振荡器的简化系统中得到了证明,但仍然需要提供完整的数学证明。在这里,我们从严格的数学观点证明,对于相同的模型,在没有延迟的情况下,同步退化-燃烧振荡相对于不同步扰动是1/不稳定的,而在存在延迟的情况下,无论其振幅有多小,2/都是渐近稳定的。为了实现这一目标,我们对该系统中的种群动力学进行了广泛的研究,特别是确定了周期轨道相对于不同步扰动的延迟依赖稳定性的机制和相关准则。另外,分析还表明,根据参数的不同,多个稳定的部分同步周期轨道可以与完全同步周期轨道共存。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Feedback-delay dependence of the stability of cluster periodic orbits in populations of degrade-and-fire oscillators with common activator.

Feedback-delay dependence of the stability of cluster periodic orbits in populations of degrade-and-fire oscillators with common activator.

Feedback-delay dependence of the stability of cluster periodic orbits in populations of degrade-and-fire oscillators with common activator.

Feedback delay has been identified as a key ingredient in the quorum sensing synchronization of synthetic gene oscillators. While this influence has been evidenced at the theoretical level in a simplified system of degrade-and-fire oscillators coupled via a common activator protein, full mathematical certifications remained to be provided. Here, we prove from a rigorous mathematical viewpoint that, for the very same model, the synchronized degrade-and-fire oscillations are 1/ unstable with respect to out-of-sync perturbations in absence of delay, and 2/ are otherwise asymptotically stable in presence of delay, no matter how small is its amplitude. To that goal, we proceed to an extensive study of the population dynamics in this system, which in particular identifies the mechanisms of, and related criteria for, the delay-dependent stability of periodic orbits with respect to out-of-sync perturbations. As an additional outcome, the analysis also reveals that, depending on the parameters, multiple stable partially synchronized periodic orbits can coexist with the fully synchronized one.

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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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