摘要
为了研究核转录因子kappa B(NF-κB)信号转导网络的内部结构和相互关联的参数对系统输出信号的影响,进行参数敏感性分析和系统模型简化是十分必要的.通过对基于TNF-α诱导的NF-κB信号转导网络数学模型进行分析,选择IKK作为系统的阶跃输入信号和NF-κBn作为系统的可测输出,利用直接微分法分析振荡输出信号NF-κBn关于64个模型参数的敏感性,并选择适当的允许误差目标函数ε,将原系统模型中的9个不敏感参数删除进行模型化简.仿真结果表明,原模型与简化模型的系统输出NF-κBn完全吻合,同时,简化模型的其余25个状态输出也与原模型的输出基本一致.因此,参数敏感性分析和模型简化结果为生物数据分析,模型建立和实验设计提供了有益的参考价值.
In order to study the impact of inner structure of biological systems and variations of correlative parameters on nuclear transcription fator-κappa B （NF-κB）signal transduction networks, it is vital to make an sensitivity analysis of system parameters and to reduce the mathematical model of NF-κB signal transduction networks, which includes 26 state variables and 64 parameters. Based on the analysis of the mathematical model of the TNFα-Induced NF-κB signal transduction networks, the IκB Kinase complex（IKK）was chosen as the step input signal of the system and NF-κB nuclear（NF-κBn）as the measurable output signal. The direct differential method （DDM）was utilized to analyse sensitivity coefficients of the oscillatory signal NF-κBn with respect to 64 parameters. Then, 9 parameters, which are less sensitive to the system output signal, were removed form mathematic model of NF-κB signaling system so as to suitably reduce the complexity of the system model. The simulation results show that the output signal NF-κBn of the reduced model has much the same oscillatory characteristic as that of the former model. On the other hand, it also can be found that the rest output signals of both models are similar on the whole Therefore, the parameters sensitivity analysis and model reduction results can give new insights to analyse biological data, to build mathematical model and to design particular experiments.
出处
《中国科学院研究生院学报》
CAS
CSCD
2007年第2期207-216,共10页
Journal of the Graduate School of the Chinese Academy of Sciences
基金
中国科学院海外杰出学者基金项目(2004-1-4)资助
关键词
敏感性分析
模型简化
NF-κB信号转导网络
直接微分法
smethodsensitivity analysis, model reduction, NF-κB signal transduction networks, the direct differential
