二维域的延迟模式形成。

IF 2.3 4区 数学 Q2 BIOLOGY
Nirmali Das, István Balázs, Bornali Das, Gergely Röst
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引用次数: 0

摘要

本研究探讨了反应扩散系统中基因表达时间延迟和结构域大小之间的相互作用如何影响时空模式的形成。为了研究这些现象,我们使用了Schnakenberg模型的修改版本,称为LI(配体内在化)模型。在一维域,已经观察到基因表达时间延迟和模式形成所需的时间之间的线性关系。我们将模型扩展到二维领域,并确认在那里也存在类似的关系。然而,我们的探索揭示了区域大小与模式出现所需时间之间的非单调相关性。在我们试图解开这些复杂动力学的过程中,我们通过考虑不同范围的初始条件来扩展我们的分析,包括空间均匀稳态的随机扰动以及来自其不稳定流形的初始函数,以观察模式形成如何展开。为了理解这些关键参数的作用,我们计算了一个关于时间延迟和域大小的双参数模式图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Delayed Pattern Formation in Two-Dimensional Domains.

This study investigates how the interaction between gene expression time delay and domain size governs spatio-temporal pattern formation in a reaction-diffusion system. To investigate these phenomena, we utilize a modified version of the Schnakenberg model called the LI (ligand internalisation) model. In a one-dimensional domain, a linear relationship has been observed between the gene expression time delay and the time it takes for patterns to form. We extend the model to the two-dimensional domain and confirm that a similar relationship holds there as well. However, our exploration reveals a non-monotonic correlation between domain size and the time required for pattern emergence. In our attempt to unravel these complex dynamics, we expand our analysis by considering a diverse range of initial conditions, including random perturbations of the spatially homogenous steady state as well as initial functions from its unstable manifold, to observe how pattern formation unfolds. To understand the role of these key parameters, we compute a two-parameter chart of patterns, with respect to time delay and domain size.

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来源期刊
CiteScore
3.90
自引率
8.60%
发文量
123
审稿时长
7.5 months
期刊介绍: The Bulletin of Mathematical Biology, the official journal of the Society for Mathematical Biology, disseminates original research findings and other information relevant to the interface of biology and the mathematical sciences. Contributions should have relevance to both fields. In order to accommodate the broad scope of new developments, the journal accepts a variety of contributions, including: Original research articles focused on new biological insights gained with the help of tools from the mathematical sciences or new mathematical tools and methods with demonstrated applicability to biological investigations Research in mathematical biology education Reviews Commentaries Perspectives, and contributions that discuss issues important to the profession All contributions are peer-reviewed.
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