基于人类信号网络和表达谱数据挖掘动脉粥样硬化相关模块  

Mining Atherosclerosis Related Modules Based on Human Singaling Network and Gene Expression Profile Data

作　　者：黄昊[1] 杜悠雯 谢瑞强[1] 侯敏[1] 冯陈晨[1] 李琬[1] 陈丽娜[1] 

机构地区：[1]哈尔滨医科大学生物信息科学与技术学院,黑龙江哈尔滨150081

出　　处：《现代生物医学进展》2015年第2期336-342,共7页Progress in Modern Biomedicine

基　　金：国家自然科学基金项目(61272388);全国大学生创新创业训练基金(201210226011);黑龙江省自然科学基金项目(F201237)

摘　　要：目的:动脉粥样硬化是一种高致死率的慢性炎症疾病,其发生和发展的机制尚不明确。本文基于人类信号网络和基因表达谱数据对动脉粥样硬化相关模块进行挖掘,以探究其在疾病发生发展中的作用机制。方法:结合人类信号网络和基因表达谱数据,设计显著差异模块筛选策略,通过功能分析,挖掘动脉粥样硬化相关模块,对动脉粥样硬化的致病机制进行研究。结果:基于网络模块的平均表达值改变量,采用两种随机方法,进行显著差异模块筛选,最终获得8个动脉粥样硬化相关的显著差异模块。结论:应用本文提出的整合筛选策略,能识别与动脉粥样硬化相关的模块,获得潜在的致病基因,并从外周血的基因表达改变来探究动脉粥样硬化致病机制,这对动脉粥样硬化的诊断、治疗以及发生发展机制的研究具有重要意义。Objective： Atherosclerosis is a chronic inflammation disease with high mortality rate, but its occurrence and development mechanism are not clear. In this paper, atherosclerosis related modules were mined based on human signaling network and gene expression profile data to explore their roles in the mechanisms of the disease development. Methods： Combined with human signaling networks and gene expression data, a strategy was designed to screen significant differential module, mine atherosclerosis related modules through functional analysis, and thus atherosclerosis pathogenic mechanismwas studied. Results： Based on the change in mean expression value as well as two kinds of stochastic methods for screening, finally eight significant differential modules closely related to atherosclerosis were obtained. Conclusion： Our integrated screening strategy could identify modules closely related to atherosclerosis, obtain potentially pathogenic genes, and explore the pathogenesis of atherosclerosis based on the changes in gene expression fi＇om peripheral blood, which could have a great significance on the treatment, mechanism and development ofatherosclerosis.

关 键 词：动脉粥样硬化 基因表达谱 人类信号网络 模块 

分 类 号：R058[医药卫生] R543.5