高维生化网络中随机性和突发性的起源。

Simon Rosenfeld
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引用次数: 13

摘要

在细胞内生物化学网络的随机动力学领域有两种主要的方法。第一种观点将注意力集中在许多对网络功能至关重要的生化成分可能只在细胞内少量存在这一事实上,因此调节过程本质上是离散的,容易出现相对较大的波动。第二种方法认为监管过程本质上是连续的。在这类过程中,由于极限环内的多稳定性和振荡运动,可能会出现复杂的伪随机行为。在本文中,我们概述了监管过程中随机性的第三种情况。这种情况只有在高维高度非线性系统中才能想象得到。特别是,我们证明了基因表达生物学中一个众所周知的现象,即突发性,是高维和高非线性耦合的自然结果。在数学术语中,突发性与描述系统动力学的随机过程的重尾概率分布有关。我们演示了“射击”噪声是如何从潜在动力系统的纯粹确定性行为中产生的。我们得出了极限随机过程可以用“重尾”广义Pareto过程精确地逼近,该过程是突发性的直接数学表达式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Origins of stochasticity and burstiness in high-dimensional biochemical networks.

Origins of stochasticity and burstiness in high-dimensional biochemical networks.

Origins of stochasticity and burstiness in high-dimensional biochemical networks.

Origins of stochasticity and burstiness in high-dimensional biochemical networks.

Two major approaches are known in the field of stochastic dynamics of intracellular biochemical networks. The first one places the focus of attention on the fact that many biochemical constituents vitally important for the network functionality may be present only in small quantities within the cell, and therefore the regulatory process is essentially discrete and prone to relatively big fluctuations. The second approach treats the regulatory process as essentially continuous. Complex pseudostochastic behavior in such processes may occur due to multistability and oscillatory motions within limit cycles. In this paper we outline the third scenario of stochasticity in the regulatory process. This scenario is only conceivable in high-dimensional highly nonlinear systems. In particular, we show that burstiness, a well-known phenomenon in the biology of gene expression, is a natural consequence of high dimensionality coupled with high nonlinearity. In mathematical terms, burstiness is associated with heavy-tailed probability distributions of stochastic processes describing the dynamics of the system. We demonstrate how the "shot" noise originates from purely deterministic behavior of the underlying dynamical system. We conclude that the limiting stochastic process may be accurately approximated by the "heavy-tailed" generalized Pareto process which is a direct mathematical expression of burstiness.

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