基于网络的复杂疾病动态表观修饰模块挖掘

项目名称： 基于网络的复杂疾病动态表观修饰模块挖掘

项目编号： No.61502363

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 计算机科学学科

项目作者： 马小科

作者单位： 西安电子科技大学

项目金额： 22万元

中文摘要： 复杂疾病是困扰人类健康的首要因素，其发病原理的揭示是疾病预防与治疗的前提，也是国际研究的热点问题。如何从多层面、多因素、时间序列等方面研究复杂疾病的发病原理，不仅具有重要的理论研究意义，而且具有重要的应用价值。本项目从遗传学与表观遗传学两个方面研究复杂疾病恶化过程中代谢路径的动态行为。项目首先利用疾病甲基化数据与基因表达数据，构建疾病恶化过程中的共甲基化与共表达时序网络；其次研究动态网络的拓扑指标，并分析甲基化与基因表达动态行为的相关性，为进一步分析网络性质提供计算手段；设计高效的疾病阶段特异性模块检测算法，并设计快速、有效的方法提取时序网络的动态模块结构；最后分析动态模块的生物功能，进一步研究关键模块在表观遗传与遗传两方面的相关性，推演动态甲基化模块与复杂疾病的关联关系。

中文关键词： 网络模体；动态功能模块；模块演化分析；基因调控网络

英文摘要： The complex disease is the leading cause for human death, and accurately identifying the mechanisms for complex diseases has been extensively studied since it is the foundation of disease prevention and therapy. Discovering the mechanism of diseases based on multiple levels, various factors as well as different time points during disease progression is valuable not only in theory research, but also in practical applications, because complexity of diseases. The ultimate goal of this project is to investigate how the pathways dynamically change during disease progression by integrating both genetic and epigenetic data. First of all, the time series co-methylated networks and co-expressed gene networks are constructed for each stage of diseases, and the correlation between genetic and epigenetic data for genes is performed based on the topological analysis is applied to the dynamic networks with an immediate purpose to pave a pathway for forthcoming analysis; Then, the efficient and effective algorithms are developed to extract disease stage specific modules. Moreover, we extend the static methods to identify the dynamic module across all the time points; Finally，we develop methods for the function prediction for dynamic module, correlation of critical dynamic modules between epigenetic and genetic profiles, as well as association study between dynamic modules and diseases.

英文关键词： network motif;dynamic functional modules;module evolutionary;gene regulation network