Zi Zhike, Cho Kwang-Hyun, Sung Myong-Hee, Xia Xuefeng, Zheng Jiashun, Sun Zhirong
Institute of Bioinformatics, MOE Key Laboratory of Bioinformatics, Department of Biological Sciences and Biotechnology, Tsinghua University, Beijing 100084, China.
FEBS Lett. 2005 Feb 14;579(5):1101-8. doi: 10.1016/j.febslet.2005.01.009.
Systems biology efforts are increasingly adopting quantitative, mechanistic modeling to study cellular signal transduction pathways and other networks. However, it is uncertain whether the particular set of kinetic parameter values of the model closely approximates the corresponding biological system. We propose that the parameters be assigned statistical distributions that reflect the degree of uncertainty for a comprehensive simulation analysis. From this analysis, we globally identify the key components and steps in signal transduction networks at a systems level. We investigated a recent mathematical model of interferon gamma induced Janus kinase-signal transducers and activators of transcription (JAK-STAT) signaling pathway by applying multi-parametric sensitivity analysis that is based on simultaneous variation of the parameter values. We find that suppressor of cytokine signaling-1, nuclear phosphatases, cytoplasmic STAT1, and the corresponding reaction steps are sensitive perturbation points of this pathway.
系统生物学研究正越来越多地采用定量的、机械的模型来研究细胞信号转导通路和其他网络。然而，该模型的特定动力学参数值集是否紧密近似相应的生物系统尚不确定。我们建议为参数分配统计分布，以反映全面模拟分析中的不确定性程度。通过此分析，我们在系统层面全局识别信号转导网络中的关键组件和步骤。我们通过应用基于参数值同时变化的多参数敏感性分析，研究了干扰素γ诱导的Janus激酶-信号转导子和转录激活子（JAK-STAT）信号通路的一个最新数学模型。我们发现细胞因子信号转导抑制因子1、核磷酸酶、细胞质STAT1以及相应的反应步骤是该通路的敏感扰动点。
