本项目拟结合多尺度数学建模和分子网络分析方法, 对病毒感染引起复杂疾病过程中调控细胞凋亡和自噬的动态分子机制进行深入研究：(1)构建病毒感染引发细胞凋亡和自噬信号网络的多尺度数学模型，利用演化算法来优化模型中的参数；(2)采用数值模拟、动力学分析和敏感性分析等方法对模型进行定性、定量的分析，研究导致细胞自噬和凋亡命运抉择的主要分子机制，并分析噪声及通路之间的交谈机制对调控细胞凋亡和自噬的影响；(3)基于高通量数据，构建病毒感染后的动态分子网络，设计算法挖掘动态网络中关键特征，从分子网络层面分析病毒感染引起复杂疾病发生、发展过程中动态分子调控机制。 本项目的实施有助于整体和系统层面上揭示病毒感染引起复杂疾病发生、发展过程中1型干扰素和内质网应激信号传导网络的动态分子调控机制。其研究成果为高效抗病毒药物研发和病毒感染引起复杂疾病的治疗提供非常重要的理论依据和科学指导。

This project tries to combine multiscale mathematical modeling and molecular network analysis to study in depth the dynamic molecular mechanism of apoptosis and autophagy in the process of complex diseases caused by virus infection. (1) Construct multiscale mathematical models based on virus infection triggered cell apoptosis and autophagy signaling network, and try to optimize parameters of the model by using evolutionary algorithms; (2) The methods such as numerical simulation, dynamic analysis as well as sensitivity analysis, etc are applied to qualitative and quantitative study of the system. Try to reveal the main molecular regulatory mechanisms underlying the choice of cell apoptosis and autophagy, and analyze the effect of noise and cross-talk between the two signaling pathways on the regulation of cell apoptosis and autophagy. (3) Based on the high-throughput data, we focus on construct dynamic network for virus infection and design new algorithm for mining key features underlying the dynamic network, we try to reveal the dynamic molecular regulatory mechanisms underlying the process of complex diseases caused by virus infection from the network level. The implementation of this project will help to elucidate the dynamic molecular regulatory mechanisms underlying virus triggered type 1 interferon and endoplasmic reticulum stress signal transduction network at both overall and systemic levels, and the research results provide theoretical basis and scientific guidance for developing of highly effective antiviral drugs and treating complex diseases related to virus infection.