A BAYESIAN NETWORK-BASED APPROACH TO CONSTRUCTING GENE REGULATORY NETWORK

摘要：

Gene regulatory networks regulate the synthesis of essence proteins involved in the key biological processes in living cells. Many methods have been advanced to reconstruct the network structure from gene expression data, such as, Boolean network models and linear models. Bayesian network (BN) models have shown the great promise in gene regulatory network reconstruction because of their capability of capturing the casual relationships between genes and handling data with noises produced in biological experiments. In this article, we first processed the data by the hierarchical clustering analysis and the inter-information entropy based analysis to classify the genes to many gene clusters. Then, we chose some gene clusters to construct the gene regulatory network and analyzed the gene network to get the bio-medical information.

关键词： The bayesian network the hierarchical clustering analysis information entropy

作者: Dong Yingli Sun Xiao Xie Jianming

作者单位: State Key Laboratory of Bioelectronics, Southeast University,Nanjing 210096,China

会议类型: 国际会议

会议名称: The 6th International Forum on Post-genome Technologies(6IFPT)(第六届国际后基因组生命科学技术学术论坛)

会议地点: 北京

会议语种:英文

页码: 163-165

在线出版日期: 2009-09-17（万方平台首次上网日期，不代表论文的发表时间）