感染性疾病调控网络的动力学模型与并行算法

项目名称： 感染性疾病调控网络的动力学模型与并行算法

项目编号： No.91230118

项目类型： 重大研究计划

立项/批准年度： 2013

项目学科： 生物物理、生化与生物分子学、生物力学与组织工程

项目作者： 邹秀芬

作者单位： 武汉大学

项目金额： 70万元

中文摘要： 感染性疾病对全球公共健康构成巨大威胁，病毒和细菌感染诱导机体炎症反应的调控网络是极其复杂的动态调控网络。本项目旨在通过对感染性疾病动态调控网络的构建与分析，提炼出可计算模型以及高维优化问题进行研究，开发满足实际精度要求的动力学模型，探索高性能的并行进化算法及其理论。具体地，以高通量的多组学数据为基础，将构建炎症因子相互作用网络转化为以蛋白表达相关性为目标函数,以基因表达特异性与关联性为约束条件的单目标优化问题求解；建立炎症因子调控网络的非线性动力学模型，探索用整数与实数变量混合的高维多目标优化问题的并行算法来识别网络的参数；研究调控网络的动力学性态与疾病表型关联的定量评估方法等。将这些方法和结果应用于识别A型流感病毒感染诱导细胞炎症反应的复杂调控网络及其分子机制，并进行生物学实验验证，为揭示感染性疾病的致病机制提供新思路。本项目形成的理论成果和计算技术可更广泛应用于其它复杂的生物学系统。

中文关键词： 系统生物学；调控网络；非线性动力学模型；并行算法；A 型流感

英文摘要： Infectious diseases are a public health threat worldwide, and viral and bacterial infection induced inflammatory regulatory networks are extremely complex and dynamical regulatory networks. The project aims at developing predictive computational models to meet the actual precision, and exploring high-performance parallel evolutionary algorithms and their theoretical basis through the research of computational modeling and high-dimensional optimization problems extracted from the construction and analysis of dynamic regulatory networks for infectious diseases. Specifically, based on the high-throughput multi-omics data, the construction of the interaction networks of inflammatory cytokines will be converted into solving a single-objective optimization problem that the correlation of protein expression as the objective function and the specificity and the relevance for gene expression as constraints. Nonlinear dynamic modeling of the inflammation regulatory networks is studied, and the parallel algorithms for high-dimensional multiobjective optimization problem with a mixture of integer and real variables to identify the parameters of the networks are designed. The quantitative method for assessing the relationship between the dynamical behavior of regulatory networks and the disease phenotypes are investigated. F

英文关键词： Systems biology；Regulation network；Nonlinear dynamical model；parallel algorithm；Influenza A virus