The mouse liver transcriptome has been extensively studied but little is known about the global hepatic gene network of the mouse under normal physiological conditions. Understanding this will help reveal the transcriptional organization of the liver and elucidate its functional complexity. Here, weighted gene co-expression network analysis (WGCNA) was carried out to explore gene co-expression networks using large-scale microarray data from normal mouse livers. A total of 7,203 genes were parsed into 16 gene modules associated with protein catabolism, RNA processing, muscle contraction, transcriptional regulation, oxidation reduction, sterol biosynthesis, translation, fatty acid metabolism, immune response and others. The modules were organized into higher order co-expression groups. Hub genes in each module were found to be critical for module function. In sum, the analyses revealed the gene modular map of the mouse liver under normal physiological condition. These results provide a systems-level framework to help understand the complexity of the mouse liver at the molecular level, and should be beneficial in annotating uncharacterized genes.