Building multiscale models with PhysiBoSS, an agent-based modeling tool

Marco Ruscone, Andrea Checcoli, Randy Heiland, Emmanuel Barillot, Paul Macklin, Laurence Calzone, Vincent Noël
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Abstract

Multiscale models provide a unique tool for studying complex processes that study events occurring at different scales across space and time. In the context of biological systems, such models can simulate mechanisms happening at the intracellular level such as signaling, and at the extracellular level where cells communicate and coordinate with other cells. They aim to understand the impact of genetic or environmental deregulation observed in complex diseases, describe the interplay between a pathological tissue and the immune system, and suggest strategies to revert the diseased phenotypes. The construction of these multiscale models remains a very complex task, including the choice of the components to consider, the level of details of the processes to simulate, or the fitting of the parameters to the data. One additional difficulty is the expert knowledge needed to program these models in languages such as C++ or Python, which may discourage the participation of non-experts. Simplifying this process through structured description formalisms -- coupled with a graphical interface -- is crucial in making modeling more accessible to the broader scientific community, as well as streamlining the process for advanced users. This article introduces three examples of multiscale models which rely on the framework PhysiBoSS, an add-on of PhysiCell that includes intracellular descriptions as continuous time Boolean models to the agent-based approach. The article demonstrates how to easily construct such models, relying on PhysiCell Studio, the PhysiCell Graphical User Interface. A step-by-step tutorial is provided as a Supplementary Material and all models are provided at: https://physiboss.github.io/tutorial/.
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利用基于代理的建模工具 PhysiBoSS 建立多尺度模型
多尺度模型为研究复杂的过程提供了一种独特的工具,它可以研究在不同空间和时间尺度上发生的事件。在生物系统的背景下,这类模型可以模拟发生在细胞内水平(如信号传递)和细胞外水平(细胞与其他细胞进行交流和协调)的机制。它们旨在了解复杂疾病中观察到的遗传或环境失调的影响,描述病理组织与免疫系统之间的相互作用,并提出恢复疾病表型的策略。构建这些多尺度模型仍然是一项非常复杂的任务,包括选择要考虑的组成部分、模拟过程的详细程度或参数与数据的拟合。另外一个困难是,用 C++ 或 Python 等语言对这些模型进行编程需要专业知识,这可能会阻碍非专业人员的参与。本文介绍了三个多尺度模型的例子,这些模型都依赖于 PhysiBoSS 框架,它是 PhysiCell 的附加组件,在基于代理的方法中包含了作为连续时间布尔模型的细胞内描述。本文演示了如何利用 PhysiCell 图形用户界面 PhysiCellStudio 轻松构建此类模型。分步教程作为补充材料提供,所有模型在 https://physiboss.github.io/tutorial/ 网站提供。
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