One of the aims of mathematical modeling is to understand and simulate the effects of biological perturbations and suggest ways to intervene and reestablish proper cell functioning. However, it remains a challenge, especially when considering the dynamics at the level of a cell population, with cells dying, dividing and interacting. Here, we introduce a novel framework for the dynamical modelling of cell populations packaged into a dedicated tool, UPMaBoSS. We rely on the preexisting tool MaBoSS, which enables probabilistic simulations of cellular networks, and add a novel layer to account for cell interactions and population dynamics. We illustrate our methodology by means of a case study dealing with TNF-induced cell death. Interestingly, the simulation of cell population dynamics with UPMaBoSS reveals a mechanism of resistance triggered by TNF treatment. This approach can be applied to diverse models of cellular networks, for example to study the impact of ligand release or drug treatments on cell fate decisions, such as commitment to proliferation, differentiation, apoptosis, etc. Relatively easy to encode, UPMaBoSS simulations require only moderate computational power and execution time. To ease the reproduction of simulations, we provide several Jupyter notebooks that can be accessed within a new release of the CoLoMoTo Docker image, which contains all required software and the example models.

中文翻译：

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UPMaBoSS：动态细胞群体建模的新框架。

数学建模的目的之一是了解和模拟生物扰动的影响，并提出干预和重建正常细胞功能的方法。然而，这仍然是一个挑战，特别是在考虑细胞死亡，分裂和相互作用的细胞群体水平的动力学时。在这里，我们介绍了一个新颖的框架，用于将细胞群体动态建模，并封装在一个专用工具UPMaBoSS中。我们依赖于预先存在的工具MaBoSS，该工具可以对蜂窝网络进行概率模拟，并添加一个新颖的层来说明细胞相互作用和种群动态。我们通过处理TNF诱导的细胞死亡的案例研究说明了我们的方法。有趣的是 UPMaBoSS对细胞群体动力学的模拟揭示了TNF治疗触发的耐药机制。这种方法可以应用于多种细胞网络模型，例如研究配体释放或药物处理对细胞命运决定的影响，例如对增殖，分化，凋亡的承诺等。相对容易编码，UPMaBoSS模拟仅需要适中的计算能力和执行时间。为了简化模拟的再现，我们提供了多个Jupyter笔记本，可以在CoLoMoTo Docker映像的新版本中进行访问，其中包含所有必需的软件和示例模型。例如，致力于增殖，分化，凋亡等。相对容易编码，UPMaBoSS仿真仅需要适度的计算能力和执行时间。为了简化模拟的再现，我们提供了多个Jupyter笔记本，可以在CoLoMoTo Docker映像的新版本中进行访问，其中包含所有必需的软件和示例模型。例如，致力于增殖，分化，凋亡等。相对容易编码，UPMaBoSS仿真仅需要适度的计算能力和执行时间。为了简化模拟的再现，我们提供了多个Jupyter笔记本，可以在CoLoMoTo Docker映像的新版本中进行访问，其中包含所有必需的软件和示例模型。