Rice (Oryza sativa) and maize (Zea mays) are the most agriculturally and economically important crops in the Poaceae. An improved understanding of complex biological relationships within Poaceae will have major implications for human and animal health, nutrition, and plant breeding strategies. A systems-genetics method that combines system biology approaches, genomics and genetics can be used to identify candidate gene sets that may be causal for complex traits. Gene co-expression networks are constructed from publicly available microarray samples and provide a systems-level view of gene co-expression. Sets of highly connected genes can be circumscribed into modules that consist of genes that exhibit functional similarity. Functional enrichment analysis of these modules provides insight into the specific processes of the underlying genes. Additionally, phenotypic enrichment analysis using data from genetic mutational studies help identify gene sets causal for complex traits. By combining gene co-expression networks with functional and phenotype enrichment analysis, we present a method to explore identification of candidate gene sets for further studies related to specific traits. We also present the first public gene co-expression network for maize, and a comparison to a previously published rice co-expression network via global alignment. This network alignment offers an exploratory view for the potential of functional and phenotypic translation between gene sets of closely related species.