基因调控网络状态描述和演化过程的SRM分析方法

项目名称： 基因调控网络状态描述和演化过程的SRM分析方法

项目编号： No.81473068

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 医药、卫生

项目作者： 易东

作者单位： 中国人民解放军第三军医大学

项目金额： 75万元

中文摘要： 生物复杂网络演化是一个连续而复杂的过程，是一个真正意义上的大数据系统，传统的网络分析方法已不能对网络状态和演化过程进行准确的描述和刻画。基于前期研究，结合国内外进展，我们认为复杂网络的演化过程应该更侧重于不同微观尺度下的观察和深入分析。本研究基于系统科学、统计学和多尺度思想，以高原习服微进化多基因调控复杂网络渐变过程为生物学背景，提出一种新的系统状态描述和评估方法－SRM。深入研究：多基因调控网络系统状态的描述方法；探索微进化过程中多基因调控网络状态的演化过程；在不同尺度上进行基因筛选差异性检验的非线性拓展；应用本课题组建立起的SRM理论框架结合高原习服微进化过程数据库进行实证研究。本项目在有效结合现场人群调查、实验室研究和理论方法的基础上，建立一种新的基因调控网络分析方法和理论框架，具有重要的应用价值，也为生物统计学方法研究提供了新的思路和方向。

中文关键词： SRM分析方法；状态描述；演化过程；基因调控网络

英文摘要： Microevolution of biological complex networks is a continuous and complex process and a really large data biological systems. So the traditional methods have not been able to describe and analyze the State and Evolution of the biological network accurately. According to our preliminary study and the development of domestic and overseas research, more focus should be put on observation and analysis to the evolutionary process of networks on multiplue time scales.This study is based on systemic science, biostatistics and multi-scale idea. The data will be extracted from the actual acclimatization process of plateau. By then, SRM, a new State Representation Methodology of system state, will be put forward. An in-depth study will be progressed upon the following aspects with our interests: to set up a system state representation method on multi-gene regulatory networks; to explore a series of analytical tools on the evolution of system states of gene regulatory networks in microevolutionary process; to extend the traditional method of screening different exprssion gene to the nonlinear method on multiscales; to finish the empirical research on gene expression regulatory networks during the microevolutionary process of altitude adaptation with all theoretical framework mentioned above.The study is an effective combination of census of population,laboratory researches and theories models. The new theoretical framework has been first time applied into the muti-gene regulatory networks of mircoevolutionary process. The results would have important practical value and could give a birth to a new thought in biostatistics.

英文关键词： SRM method;states description;evolutionary process;gene regulation networks