Combining experiments with multi-cell agent-based modeling to study biological tissue patterning
Combining experiments with multi-cell agent-based modeling to study biological tissue patterning
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DOI：
10.1093/bib/bbm024
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发表时间：
2007-07-01
影响因子：
9.5
通讯作者：
Peirce, Shayn M.
中科院分区：
文献类型：
--
作者：
Thorne, Bryan C.;Bailey, Alexander M.;Peirce, Shayn M.
基于代理的建模（ABM），也被称为“基于个体的建模（IBM-based modeling）”，是一种计算方法，它模拟自治实体（代理或个体细胞）之间的相互作用及其局部环境，以预测更高级别的涌现模式。一个文献衍生的规则集管理每个个体代理的行为。虽然这项技术已被广泛用于生态和社会科学，但它只是最近才被应用于生物医学研究。这篇评论的目的是提供一个介绍ABM，因为它已被用来研究复杂的多细胞生物学现象，强调耦合模型与实验工作的重要性，并概述了未来的挑战ABM领域及其在生物医学研究中的应用。我们强调了一些已发表的ABM的例子，专注于工作，结合实验与ABM分析，以及这种配对如何产生新的理解。最后，我们提出了推进这一并行办法的建议。
Agent-based modeling (ABM), also termed `Individual-based modeling (IBM)', is a computational approach that simulates the interactions of autonomous entities (agents, or individual cells) with each other and their local environment to predict higher level emergent patterns. A literature-derived rule set governs the actions of each individual agent. While this technique has been widely used in the ecological and social sciences, it has only recently been applied in biomedical research. The purpose of this review is to provide an introduction to ABM as it has been used to study complex multi-cell biological phenomena, underscore the importance of coupling models with experimental work, and outline future challenges for the ABM field and its application to biomedical research. We highlight a number of published examples of ABM, focusing on work that has combined experimental with ABM analyses and how this pairing produces new understanding. We conclude with suggestions for moving forward with this parallel approach.