Hong Tian
Department of Biological Sciences, The University of Texas at Dallas, Richardson, TX, USA.
Methods Mol Biol. 2025;2883:155-165. doi: 10.1007/978-1-0716-4290-0_7.
In this chapter, we first survey strategies for the mathematical modeling of gene regulatory networks for capturing physiologically important dynamics in cells such as oscillations. We focus on models based on ordinary differential equations with various forms of nonlinear functions that describe gene regulations. We next use a small system of a microRNA and its mRNA target to illustrate a recently discovered oscillator driven by noncoding RNAs. This oscillator has unique features that distinguish it from conventional biological oscillators, including the absence of an imposed negative feedback loop and the divergence of the periods. The latter property may serve crucial biological functions for restoring heterogeneity of cell populations on the timescale of days. We describe general requirements for obtaining the limit cycle oscillations in terms of underlying biochemical reactions and kinetic rate constants. We discuss future directions stemming from this minimal, noncoding RNA-based model for gene expression oscillation.
在本章中，我们首先概述基因调控网络数学建模的策略，以捕捉细胞中生理上重要的动态变化，如振荡。我们重点关注基于常微分方程且具有描述基因调控的各种非线性函数形式的模型。接下来，我们使用一个微小RNA及其mRNA靶标的小系统，来说明一种最近发现的由非编码RNA驱动的振荡器。这种振荡器具有独特的特征，使其有别于传统的生物振荡器，包括不存在强加的负反馈回路以及周期的发散。后一种特性可能在数天的时间尺度上对恢复细胞群体的异质性起着关键的生物学作用。我们根据潜在的生化反应和动力学速率常数描述了获得极限环振荡的一般要求。我们讨论了源于这个基于非编码RNA的基因表达振荡最小模型的未来方向。
