MaizeNet is a genome-scale co-functional network of maize (Zea mays) genes. Therefore, genes that are direct neighbors or proximal in the network are likely to function in the same biological process. MaizeNet was constructed by integrating 21 component networks where each network was inferred from different omics data. By the integration of heterogeneous data, MaizeNet provides comprehensive view of the genetic architecture in maize. Applying network analysis algorithms allows the MaizeNet to prioritize candidate genes for a particular biological process. The prioritization service implemented in MaizeNet can be exploited to generate novel functional hypothesis, narrow down candidate genes, and identify new genes for the function. This will benefit maize genetics research because of technical difficulty in forward and reverse genetics approaches to study complex maize traits such as drought tolerance and biomass.