Computational Biomodeling Laboratory, Turku Centre for Computer Science, Finland; Department of Computer Science, Åbo Akademi University, Finland.
Computational Biomodeling Laboratory, Turku Centre for Computer Science, Finland; Department of Mathematics and Statistics, University of Turku, Finland; National Institute for Research and Development in Biological Sciences, Romania.
Comput Biol Med. 2019 Mar;106:91-96. doi: 10.1016/j.compbiomed.2019.01.016. Epub 2019 Jan 24.
The construction of large scale biological models is a laborious task, which is often addressed by adopting iterative routines for model augmentation, adding certain details to an initial high level abstraction of the biological phenomenon of interest. Refitting a model at every step of its development is time consuming and computationally intensive. The concept of model refinement brings about an effective alternative by providing adequate parameter values that ensure the preservation of its quantitative fit at every refinement step. We demonstrate this approach by constructing the largest-ever refinement-based biomodel, consisting of 421 species and 928 reactions. We start from an already fit, relatively small literature model whose consistency we check formally. We then construct the final model through an algorithmic step-by-step refinement procedure that ensures the preservation of the model's fit.
大规模生物模型的构建是一项艰巨的任务，通常通过采用迭代例程来进行模型扩充，为感兴趣的生物现象的初始高级抽象添加某些细节。在模型开发的每一步都重新调整模型既费时又费计算资源。模型细化的概念通过提供足够的参数值提供了一种有效的替代方法，这些参数值可确保在每个细化步骤都保持其定量拟合。我们通过构建迄今为止最大的基于细化的生物模型来证明这种方法，该模型由 421 个物种和 928 个反应组成。我们从一个已经拟合的、相对较小的文献模型开始，我们正式检查其一致性。然后，我们通过算法逐步细化过程构建最终模型，以确保模型拟合的保持。
