Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas.
Am J Physiol Cell Physiol. 2023 Feb 1;324(2):C247-C262. doi: 10.1152/ajpcell.00185.2022. Epub 2022 Dec 12.
Physiological processes rely on the control of cell proliferation, and the dysregulation of these processes underlies various pathological conditions, including cancer. Mathematical modeling can provide new insights into the complex regulation of cell proliferation dynamics. In this review, we first examine quantitative experimental approaches for measuring cell proliferation dynamics in vitro and compare the various types of data that can be obtained in these settings. We then explore the toolbox of common mathematical modeling frameworks that can describe cell behavior, dynamics, and interactions of proliferation. We discuss how these wet-laboratory studies may be integrated with different mathematical modeling approaches to aid the interpretation of the results and to enable the prediction of cell behaviors, specifically in the context of cancer.
生理过程依赖于细胞增殖的控制，这些过程的失调是各种病理状况的基础，包括癌症。数学建模可以为细胞增殖动力学的复杂调控提供新的见解。在这篇综述中，我们首先检查了定量实验方法，以测量体外细胞增殖动力学，并比较了在这些环境下可以获得的各种类型的数据。然后，我们探讨了常见的数学建模框架的工具包，这些框架可以描述细胞行为、动力学和增殖的相互作用。我们讨论了如何将这些湿实验室研究与不同的数学建模方法相结合，以帮助解释结果，并能够预测细胞行为，特别是在癌症的背景下。
