近期的Omics数据的可用性使得构建众多角色扮演生物分子之间的整体互动图成为可能。然而，这些网络通常是静态的，忽略了生物过程的动态行为。另一方面，动态模型通常是小规模构建的。因此，构建能够量化预测时间课程细胞行为的大规模动态模型仍然是一个巨大的挑战。本研究提出了一个流程，用于自动构建大规模动态模型。该流程采用给定现象中一系列生物分子及其时间课程轨迹作为输入。首先，构建生物分子的互动网络。为了说明每个互动的基础分子事件，将其转化为生化反应图。接下来，为每个涉及的生物分子定义反应动力学方程（ODE）。最后，通过一种新颖的大规模参数近似方法估计ODE系统的参数。模拟大肠癌细胞系对不同化疗方案的响应，证明了该流程的高性能。总之，系统蛋白质关联动态分析仪构建了基因组水平的动态模型，填补了大规模静态和小规模动态建模策略之间的差距。这种模拟方法允许进行全面的定量预测，对于精准医疗中治疗干预的模拟至关重要。有关构建的大规模结肠癌模型的详细信息可在补充数据中获得。SPADAN工具箱源代码也可以在GitHub（https://github.com/PooyaBorzou/SPADAN）上找到。补充数据可在Bioinformatics在线获取。©2023年作者（们）发表于牛津大学出版社。

The recent availability of omics data allows the construction of holistic maps of interactions between numerous role-playing biomolecules. However, these networks are often static, ignoring the dynamic behavior of biological processes. On the other hand, dynamic models are commonly constructed on small scales. Hence, the construction of large-scale dynamic models that can quantitatively predict the time-course cellular behaviors remains a big challenge.In this study, a pipeline is proposed for the automatic construction of large-scale dynamic models. The pipeline uses a list of biomolecules and their time-course trajectories in a given phenomenon as input. First, the interaction network of the biomolecules is constructed. To state the underlying molecular events of each interaction, it is translated into a map of biochemical reactions. Next, to define the kinetics of the reactions, an ordinary differential equation (ODE) is generated for each involved biomolecule. Finally, the parameters of the ODE system are estimated by a novel large-scale parameter approximation method. The high performance of the pipeline is demonstrated by modeling the response of a colorectal cancer cell line to different chemotherapy regimens. In conclusion, Systematic Protein Association Dynamic ANalyzer constructs genome-scale dynamic models, filling the gap between large-scale static and small-scale dynamic modeling strategies. This simulation approach allows for holistic quantitative predictions which are critical for the simulation of therapeutic interventions in precision medicine.Detailed information about the constructed large-scale model of colorectal cancer is available in supplementary data. The SPADAN toolbox source code is also available on GitHub (https://github.com/PooyaBorzou/SPADAN).Supplementary data are available at Bioinformatics online.© The Author(s) 2023. Published by Oxford University Press.