Mendoza Luis, Pardo Fátima
Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico, Mexico.
Theory Biosci. 2010 Dec;129(4):283-93. doi: 10.1007/s12064-010-0112-x. Epub 2010 Oct 5.
There is a wealth of information regarding the differentiation of T-helper cells. Nevertheless, there is no general agreement on the topology and dynamical properties of the molecular network controlling the differentiation of these cells. This paper presents a continuous dynamical system to model the signaling network that controls the differentiation process of T-helper cells. The model is able to represent the differentiation from the precursor Th0 cell to any of the four effectors types (Th1, Th2, Th17, and Treg), as well as the phenotype of single null mutants. We present the first sensitivity analysis of the equations defining the Th model, showing that the qualitative dynamical behavior of the model is very robust against changes in three out of four tested parameters. The robustness of the model is in agreement with our claim that the qualitative behavior of the system is to a large extent independent of the methodological framework used for modeling.
关于辅助性T细胞的分化,存在大量信息。然而,对于控制这些细胞分化的分子网络的拓扑结构和动力学特性,尚无普遍共识。本文提出了一个连续动力学系统,用于模拟控制辅助性T细胞分化过程的信号网络。该模型能够表示从前体Th0细胞到四种效应器类型(Th1、Th2、Th17和Treg)中任何一种的分化,以及单个无效突变体(基因敲除突变体)的表型。我们对定义Th模型的方程进行了首次敏感性分析,结果表明,该模型的定性动力学行为对于四个测试参数中的三个参数的变化具有很强的鲁棒性。该模型的鲁棒性与我们的观点一致,即系统的定性行为在很大程度上独立于用于建模的方法框架。