应用关联规则挖掘构建人小脑发育的基因表达关联网络  

Constructing Association Networks from Development Cerebella Microarray Data Based on Association Rule Mining

作　　者：彭斌[1] 杨忠[2] 李辉智[3] 易东[1] 

机构地区：[1]第三军医大学卫生统计教研室,400038 [2]第三军医大学神经生物教研室 [3]西南政法大学刑侦学院

出　　处：《中国卫生统计》2007年第2期117-119,123,共4页Chinese Journal of Health Statistics

基　　金：国家自然基金资助课题(编号:60371034)

摘　　要：目的构建小脑发育过程中基因之间的表达调控关联网络。方法应用关联规则(Association Rules)挖掘技术和GO(Gene Ontology)数据库对人胎儿小脑发育的基因芯片数据进行分析处理。结果根据胎儿6个不同发育时间段的基因芯片数据从10080个基因(或EST片段)中筛选出110个表达变异较大的基因作为输入,得到形如LHSRHS的关联规则5000多条;从中选择10个功能已知且在关联规则中出现频率较高的基因作为构建关联网络的基因。根据包含这10个基因的关联规则,构建出两张基因表达关联网络图。结论利用关联规则挖掘技术构建的小脑发育基因表达关联网络在一定程度上能够描述小脑发育过程中基因之间的关联关系。Objective The purpose of this study was to construct association networks from fetuses development cerebella microarray data. Methods Using association rules mining technique and GO （Gene Ontology） to analyze the microarray data. Results We got 110 genes or ESTs whose expression levels varied significantly on 6 periods of fetuses＇ cerebella development from total 10080 genes or ESTs. As a result, about 5 000 association rules formed as LHS→RHS were found. According to all association rules of 10 selected genes whose functions were known, two figures about association networks of genes expression were drawn. Conclusion The association networks of fetuses＇ cerebella development which based on association rules were somewhat able to describe the relationship among genes during cerebella development.

关 键 词：关联规则 基因芯片数据 关联网络 小脑发育 

分 类 号：R741[医药卫生—神经病学与精神病学]