Resource Facility for Population Kinetics, Department of Bioengineering Box 355061, University of Washington, Seattle, WA 98195-5061, United States.
J Theor Biol. 2010 May 21;264(2):528-37. doi: 10.1016/j.jtbi.2010.02.029. Epub 2010 Feb 24.
Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology.
(1) 模拟以预测实验结果，(2) 从关于生物系统未观察到方面的实验数据中进行推断，即参数估计。虽然前者的目的在生物科学中已经很常见，但后者则不那么常见，特别是在研究细胞和亚细胞现象（如信号转导——当前研究的焦点）时。在这个层面上，数据很难获得。因此，即使是相对简单的模型也可能包含参数，而这些参数的可用数据不足以进行估计。在本研究中，我们使用一组已发表的细胞信号模型来解决与全局参数可识别性相关的问题。也就是说，我们要回答以下问题：假设模型某些变量的已知时间过程，从理论上讲，即使有连续的、无噪声的数据，哪些参数是无法估计的？在介绍这个问题及其相关性之后，我们使用 DAISY（用于系统可识别性的微分代数）对一组细胞信号模型进行了完整的可识别性分析。我们利用我们的分析揭示了在常微分方程（ODE）模型中参数可识别性方面的重要问题。我们认为，这在生物建模中，特别是在细胞生物学中，是一个尚未被充分认识的问题。
