Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Systems Biology Laboratory, School of Mathematics and Statistics, and Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia.
PLoS Comput Biol. 2021 May 13;17(5):e1008859. doi: 10.1371/journal.pcbi.1008859. eCollection 2021 May.
Simulating complex biological and physiological systems and predicting their behaviours under different conditions remains challenging. Breaking systems into smaller and more manageable modules can address this challenge, assisting both model development and simulation. Nevertheless, existing computational models in biology and physiology are often not modular and therefore difficult to assemble into larger models. Even when this is possible, the resulting model may not be useful due to inconsistencies either with the laws of physics or the physiological behaviour of the system. Here, we propose a general methodology for composing models, combining the energy-based bond graph approach with semantics-based annotations. This approach improves model composition and ensures that a composite model is physically plausible. As an example, we demonstrate this approach to automated model composition using a model of human arterial circulation. The major benefit is that modellers can spend more time on understanding the behaviour of complex biological and physiological systems and less time wrangling with model composition.
模拟复杂的生物和生理系统，并预测它们在不同条件下的行为仍然具有挑战性。将系统分解为更小、更易于管理的模块可以解决这个问题，同时有助于模型开发和模拟。然而，生物学和生理学中的现有计算模型通常不是模块化的，因此难以组合成更大的模型。即使这是可能的，由于与物理定律或系统的生理行为不一致，所得到的模型也可能没有用处。在这里，我们提出了一种用于组合模型的通用方法，将基于能量的键合图方法与基于语义的注释相结合。这种方法提高了模型组合的效率，并确保了组合模型在物理上是合理的。作为一个例子，我们使用人体动脉循环模型展示了这种自动模型组合方法。主要的好处是，建模者可以花更多的时间来理解复杂的生物和生理系统的行为，而不必花费更多的时间来处理模型组合。
