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多尺度分析和生物系统中群体迁移的建模。

Multi-scale analysis and modelling of collective migration in biological systems.

机构信息

Department of Innovative Methods of Computing, Center for Information Services and High Performance Computing, Technische Universität Dresden, Dresden, Germany.

Department of Cell Biology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands.

出版信息

Philos Trans R Soc Lond B Biol Sci. 2020 Sep 14;375(1807):20190377. doi: 10.1098/rstb.2019.0377. Epub 2020 Jul 27.

Abstract

Collective migration has become a paradigm for emergent behaviour in systems of moving and interacting individual units resulting in coherent motion. In biology, these units are cells or organisms. Collective cell migration is important in embryonic development, where it underlies tissue and organ formation, as well as pathological processes, such as cancer invasion and metastasis. In animal groups, collective movements may enhance individuals' decisions and facilitate navigation through complex environments and access to food resources. Mathematical models can extract unifying principles behind the diverse manifestations of collective migration. In biology, with a few exceptions, collective migration typically occurs at a 'mesoscopic scale' where the number of units ranges from only a few dozen to a few thousands, in contrast to the large systems treated by statistical mechanics. Recent developments in multi-scale analysis have allowed linkage of mesoscopic to micro- and macroscopic scales, and for different biological systems. The articles in this theme issue on 'Multi-scale analysis and modelling of collective migration' compile a range of mathematical modelling ideas and multi-scale methods for the analysis of collective migration. These approaches (i) uncover new unifying organization principles of collective behaviour, (ii) shed light on the transition from single to collective migration, and (iii) allow us to define similarities and differences of collective behaviour in groups of cells and organisms. As a common theme, self-organized collective migration is the result of ecological and evolutionary constraints both at the cell and organismic levels. Thereby, the rules governing physiological collective behaviours also underlie pathological processes, albeit with different upstream inputs and consequences for the group. This article is part of the theme issue 'Multi-scale analysis and modelling of collective migration in biological systems'.

摘要

群体迁移已成为移动和相互作用的个体单元系统中涌现行为的范例,导致连贯的运动。在生物学中,这些单元是细胞或生物体。细胞的集体迁移在胚胎发育中很重要,它是组织和器官形成的基础,也是病理过程,如癌症侵袭和转移的基础。在动物群体中,集体运动可以增强个体的决策能力,并有助于在复杂环境中导航和获取食物资源。数学模型可以提取出集体迁移多样性表现背后的统一原理。在生物学中,除了少数例外,集体迁移通常发生在“介观尺度”上,其中单元的数量从几十个到几千个不等,与统计力学处理的大系统形成对比。多尺度分析的最新发展允许将介观尺度与微观和宏观尺度联系起来,并适用于不同的生物系统。本期主题为“集体迁移的多尺度分析与建模”的文章汇集了一系列数学建模思想和多尺度方法,用于分析集体迁移。这些方法(i)揭示了集体行为新的统一组织原则,(ii)阐明了从单细胞到集体迁移的转变,(iii)使我们能够定义细胞和生物体群体中集体行为的相似性和差异性。作为一个共同的主题,自组织的集体迁移是细胞和生物体水平上生态和进化约束的结果。因此,控制生理集体行为的规则也构成了病理过程的基础,尽管其上游输入和对群体的影响不同。本文是主题为“生物系统中集体迁移的多尺度分析与建模”的一部分。

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3
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