基于基因表达谱与GO的共调控基因挖掘

In this paper we propose a new similarity measure based on subspace search.It firstly searches for the spatial correlation of the gene, and then calculate the similarity of the gene expression levels in the sub-space.Thus can better reflect the spatial information of gene expression.Gene function classification system (Gene Ontology) provides a unified annotation for the genes,it is a controlled vocabulary used to describe molecular function, biological process and cellular component of genes and gene products in a generic cell. The study on gene regulatory networks is a hot topic problem on functional genomics;they reveal complicated life phenomena from the regulating mechanism among genes.By researching of gene regulatory networks,the thesis attempted to use both gene expression profiles and GO annotation information to construct the gene regulatory networks, then use the networks mining co-regulated genes.The results show that this method has a good potential application, the integration of information can provide valuable information for constructing gene regulatory network.