奇异扰动域中的细胞扩散过程

IF 2.2 4区 数学 Q2 BIOLOGY
Paul C Bressloff
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引用次数: 0

摘要

细胞生物学中有许多过程可以用粒子在二维(2D)或三维(3D)有界域 Ω ⊂ R d 中扩散来建模,该有界域包含一组小的子域或内部区室 U j , j = 1 , ... , N(奇异扰动扩散问题)。域 Ω 可以代表细胞膜、细胞质、细胞核或细胞外体积,而单个区室可以代表突触、膜蛋白簇、生物凝聚物或法定量感应细菌细胞。在这篇综述中,我们结合使用了匹配渐近分析和格林函数方法来求解二维和三维奇异边界值问题(BVP),其中每个内部边界 ∂ U j 都施加了非均质罗宾条件。这样,我们就可以将以往对奇异扰动扩散问题的各种研究纳入一个数学建模框架。我们主要关注稳态解和通向稳态的方法,但也强调了当前在处理随时间变化的解和随机切换过程时所面临的一些挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cellular diffusion processes in singularly perturbed domains.

There are many processes in cell biology that can be modeled in terms of particles diffusing in a two-dimensional (2D) or three-dimensional (3D) bounded domain Ω R d containing a set of small subdomains or interior compartments U j , j = 1 , , N (singularly-perturbed diffusion problems). The domain Ω could represent the cell membrane, the cell cytoplasm, the cell nucleus or the extracellular volume, while an individual compartment could represent a synapse, a membrane protein cluster, a biological condensate, or a quorum sensing bacterial cell. In this review we use a combination of matched asymptotic analysis and Green's function methods to solve a general type of singular boundary value problems (BVP) in 2D and 3D, in which an inhomogeneous Robin condition is imposed on each interior boundary U j . This allows us to incorporate a variety of previous studies of singularly perturbed diffusion problems into a single mathematical modeling framework. We mainly focus on steady-state solutions and the approach to steady-state, but also highlight some of the current challenges in dealing with time-dependent solutions and randomly switching processes.

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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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