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 One. 2022 Jun 3;17(6):e0269497. doi: 10.1371/journal.pone.0269497. eCollection 2022.
Hierarchical modelling is essential to achieving complex, large-scale models. However, not all modelling schemes support hierarchical composition, and correctly mapping points of connection between models requires comprehensive knowledge of each model's components and assumptions. To address these challenges in integrating biosimulation models, we propose an approach to automatically and confidently compose biosimulation models. The approach uses bond graphs to combine aspects of physical and thermodynamics-based modelling with biological semantics. We improved on existing approaches by using semantic annotations to automate the recognition of common components. The approach is illustrated by coupling a model of the Ras-MAPK cascade to a model of the upstream activation of EGFR. Through this methodology, we aim to assist researchers and modellers in readily having access to more comprehensive biological systems models.
层次建模对于实现复杂的大规模模型至关重要。然而，并非所有建模方案都支持层次组合，正确映射模型之间的连接点需要对每个模型的组件和假设有全面的了解。为了解决在整合生物仿真模型时遇到的这些挑战，我们提出了一种自动且自信地组合生物仿真模型的方法。该方法使用键合图将物理和热力学建模的各个方面与生物学语义结合起来。我们通过使用语义注释来自动识别常见组件，改进了现有的方法。我们通过将 Ras-MAPK 级联模型与 EGFR 上游激活模型进行耦合来说明该方法。通过这种方法，我们旨在帮助研究人员和建模人员轻松获得更全面的生物系统模型。
