Cells in Silico - introducing a high-performance framework for large-scale tissue modeling.
Cells in Silico - introducing a high-performance framework for large-scale tissue modeling.
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DOI：
10.1186/s12859-020-03728-7
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发表时间：
2020-10-06
影响因子：
3
通讯作者：
Schug A
中科院分区：
文献类型：
--
作者：
Berghoff M;Rosenbauer J;Hoffmann F;Schug A
细胞动力学和组织发育方面的发现不断重塑我们对基本生物学过程的理解，如胚胎发生、伤口愈合和肿瘤发生。高质量的显微镜数据和对单细胞效应不断提高的理解迅速加速了新的发现。尽管如此，许多计算模型要么非常详细地描述少数细胞，要么更粗略地描述较大的细胞群和组织。在这里，我们将这两个尺度连接在一个联合理论模型中。我们开发了一个高度并行的细胞波茨模型，它可以灵活地应用，并提供了一个基于代理的驱动细胞事件的模型。该模型可以模块化扩展到两个尺度上的多模型模拟。基于NAStJA框架，实现了在高性能计算系统上高效运行的扩展实现。我们在我们的方法中证明了偏差的独立性以及出色的缩放行为。我们的模型在超过10,000个核的情况下近似线性扩展，因此仅受可用计算资源的限制，可以模拟大规模的三维组织。严格的模块化设计允许任意模型灵活配置，并使应用程序在广泛的研究问题。硅细胞（CiS）可以很容易地被塑造成不同的模型假设，并有助于推动计算科学家将他们的模拟扩展到组织模拟的新领域。作为一个例子，我们强调在亚细胞分辨率10003体素大小的癌组织模拟。
Discoveries in cellular dynamics and tissue development constantly reshape our understanding of fundamental biological processes such as embryogenesis, wound-healing, and tumorigenesis. High-quality microscopy data and ever-improving understanding of single-cell effects rapidly accelerate new discoveries. Still, many computational models either describe few cells highly detailed or larger cell ensembles and tissues more coarsely. Here, we connect these two scales in a joint theoretical model. We developed a highly parallel version of the cellular Potts model that can be flexibly applied and provides an agent-based model driving cellular events. The model can be modular extended to a multi-model simulation on both scales. Based on the NAStJA framework, a scaling implementation running efficiently on high-performance computing systems was realized. We demonstrate independence of bias in our approach as well as excellent scaling behavior. Our model scales approximately linear beyond 10,000 cores and thus enables the simulation of large-scale three-dimensional tissues only confined by available computational resources. The strict modular design allows arbitrary models to be configured flexibly and enables applications in a wide range of research questions. Cells in Silico (CiS) can be easily molded to different model assumptions and help push computational scientists to expand their simulations to a new area in tissue simulations. As an example we highlight a 10003 voxel-sized cancerous tissue simulation at sub-cellular resolution.