Drosophila is one of the most widely studied model organisms. Along with this distinction comes a staggering amount of experimental data. Data regarding gene expression and regulation, protein interaction, genetic interaction, and phenotypic annotation for D. melanogaster were gathered. We processed these data and computed relationships between gene pairs across all datasets. The data were then integrated into the form of a network, where nodes represent genes and the undirected edges represent functional relationships. The integrated network was tested for coherence with respect to previously determined functional annotations and molecular pathways. We show that this integrated network offers insights into the complexity of gene interactions compared to networks built while excluding individual data sets. We then employ the network to make predictions on unannotated genes.