中文摘要：

基于流感病毒H3N2的高通量数据,建立了S1PR1介导的细胞因子释放的信号通路的非线性常微分方程组模型,并用基于梯度的差分进化算法（DMGBDE）来识别模型中的参数.数值模拟结果表明：所建立的数学模型能够很好地吻合实验数据.进一步的计算分析表明细胞因子在病毒感染后出现症状和未出现症状的2类人群中呈现显著不同的动力学过程和稳态水平.参数敏感性分析揭示了病毒感染人体后是否会出现严重临床症状的重要因素.这些结果可为阐明流感病毒感染致病的分子生物学机制提供理论指导.

英文摘要：

Based on the high-throughput data of H3N2 influenza virus,a nonlinear ordinary differential equations（ ODEs） model for S1PR1-mediated cytokines release signaling pathway is built. The parameters in the model are identified using the gradient-based differential evolution（ DE） algorithm（ DMGBDE）. Numerical simulation results show that the constructed mathematical model can fit the experimental data very well. Moreover,computational analyses demonstrate that cytokines exhibit significantly different dynamical processes and steady state levels between the asymptomatic and symptomatic people who were infected by influenza virus. In addition,parameters sensitivity analysis reveals the important factors whether the virus-infected people have severe clinical symptoms. These results can provide theoretical direction for clarifying the molecular pathogenic mechanisms of influenza virus infections.