针对阿尔茨海默症(AD) 起病隐匿、进行性病程长、发病机理复杂、以及其分子水平的基因信号传导通路及调控关系难以重建等特征，提出：以脑部炎症这一AD核心病理机制为主线，运用生物信息学方法，探寻脑部炎症基因信号传导及调控机制对AD产生和发展的影响，探索构建AD基因调控网络的方法，为AD致病机理的研究提供参考。研究内容包括：1)探索多源异构生物数据的抽取、转换和加载的数据融合模型，构建面向AD的数据整合平台；2)研究与炎症反应密切相关的AD特征基因提取方法，利用生物信息学方法探索炎症反应基因信号传导通路作用于AD致病基因表达的机理；3)提出基因调控网络构建的模块化及优化方法，并提出优化调整策略；4)研究和揭示AD基因调控网络的动态演化规律，并形成生物学家易于理解的表达形式。该项目的研究将为加速AD等重大疾病医学早期诊断、治疗、预防以及推动制药工程的发展提供重要的研究方法和手段。

Alzheimer's disease (AD) are characterized by its hidden onset, long progressive course, complex pathological mechanism, and the difficulties of reconstruction of the genes signal pathways and its regulatory network. In our proposal we use bioinformatical methods to study the reconstruction of the AD gene regulatory network, and deduce the mechanism of inflammatory gene pathways and regulatory functions acting on AD based on the main pathological mechanism of AD- inflammatory reactions. Our study includes: 1) study the integration model of the extraction, transforming and loading of multi-source and heterogeneous biological datasets, and built the AD biological datasets integration platforms; 2)study the feature extraction methods of significant genes of AD which related to inflammation, and deduce the mechanism of inflammatory gene pathways and regulatory functions acting on AD; 3)propose the modulization and optimization methods of the gene regulatory network and present the optimal adjusting rules; 4) explore the dynamic evolution law of pathological mechanism of AD and make them available to biologists. We believe that our study gives a novel and valuable method for the research of early detection, therapy, prevent of diseases and accelerate the development of pharmacy engineering.