Cooling Michael T, Nickerson David P, Nielsen Poul M F, Hunter Peter J
Auckland Bioengineering Institute, the University of Auckland, New Zealand.
Department of Engineering Science, the University of Auckland, New Zealand.
J Physiol. 2016 Dec 1;594(23):6817-6831. doi: 10.1113/JP272633. Epub 2016 Aug 29.
The complexity of computational models is increasing, supported by research in modelling tools and frameworks. But relatively little thought has gone into design principles for complex models. We propose a set of design principles for complex model construction with the Physiome standard modelling protocol CellML. By following the principles, models are generated that are extensible and are themselves suitable for reuse in larger models of increasing complexity. We illustrate these principles with examples including an architectural prototype linking, for the first time, electrophysiology, thermodynamically compliant metabolism, signal transduction, gene regulation and synthetic biology. The design principles complement other Physiome research projects, facilitating the application of virtual experiment protocols and model analysis techniques to assist the modelling community in creating libraries of composable, characterised and simulatable quantitative descriptions of physiology.
The ability to produce and customise complex computational models has great potential to have a positive impact on human health. As the field develops towards whole-cell models and linking such models in multi-scale frameworks to encompass tissue, organ, or organism levels, reuse of previous modelling efforts will become increasingly necessary. Any modelling group wishing to reuse existing computational models as modules for their own work faces many challenges in the context of construction, storage, retrieval, documentation and analysis of such modules. Physiome standards, frameworks and tools seek to address several of these challenges, especially for models expressed in the modular protocol CellML. Aside from providing a general ability to produce modules, there has been relatively little research work on architectural principles of CellML models that will enable reuse at larger scales. To complement and support the existing tools and frameworks, we develop a set of principles to address this consideration. The principles are illustrated with examples that couple electrophysiology, signalling, metabolism, gene regulation and synthetic biology, together forming an architectural prototype for whole-cell modelling (including human intervention) in CellML. Such models illustrate how testable units of quantitative biophysical simulation can be constructed. Finally, future relationships between modular models so constructed and Physiome frameworks and tools are discussed, with particular reference to how such frameworks and tools can in turn be extended to complement and gain more benefit from the results of applying the principles.
在建模工具和框架研究的支持下,计算模型的复杂性正在增加。但对于复杂模型的设计原则却相对缺乏思考。我们提出了一套使用生理组标准建模协议CellML构建复杂模型的设计原则。遵循这些原则生成的模型具有可扩展性,并且自身适合在日益复杂的更大模型中重复使用。我们通过示例来说明这些原则,其中包括一个架构原型,该原型首次将电生理学、热力学兼容的代谢、信号转导、基因调控和合成生物学联系起来。这些设计原则补充了其他生理组研究项目,有助于虚拟实验协议和模型分析技术的应用,以协助建模社区创建可组合、有特征且可模拟的生理学定量描述库。
生成和定制复杂计算模型的能力对人类健康具有巨大的积极影响潜力。随着该领域朝着全细胞模型发展,并在多尺度框架中将此类模型联系起来以涵盖组织、器官或生物体层面,重复使用先前的建模成果将变得越来越必要。任何希望将现有计算模型作为模块用于自身工作的建模团队,在构建、存储、检索、记录和分析此类模块方面都面临诸多挑战。生理组标准、框架和工具旨在应对其中的一些挑战,特别是对于以模块化协议CellML表示的模型。除了提供生成模块的一般能力外,关于能够实现更大规模重复使用的CellML模型架构原则的研究工作相对较少。为了补充和支持现有的工具和框架,我们制定了一套原则来解决这一问题。通过将电生理学、信号传导、代谢、基因调控和合成生物学相结合的示例来说明这些原则,共同形成了CellML中全细胞建模(包括人为干预)的架构原型。此类模型展示了如何构建可测试的定量生物物理模拟单元。最后,讨论了如此构建的模块化模型与生理组框架和工具之间未来的关系,特别提及此类框架和工具如何反过来进行扩展,以补充并从应用这些原则的结果中获得更多益处。