Monocytes and macrophages differentiate from progenitor cells under the influence of colony-stimulating factors. Genome-scale data have enabled the identification of the sets of genes that are associated with specific functions and the mechanisms by which thousands of genes are regulated in response to pathogen challenge. In large datasets, it is possible to identify large sets of genes that are coregulated with the transcription factors that regulate them. They include macrophage-specific genes, interferon-responsive genes, early inflammatory genes, and those associated with endocytosis. Such analyses can also extract macrophage-associated signatures from large cancer tissue datasets. However, cluster analysis provides no support for a signature that distinguishes macrophages from antigen-presenting dendritic cells, nor the classification of macrophage activation states as classical versus alternative, or M1 versus M2. Although there has been a focus on a small subset of lineage-enriched transcription factors, such as PU.1, more than half of the transcription factors in the genome can be expressed in macrophage lineage cells under some state of activation, and they interact in a complex network. The network architecture is conserved across species, but many of the target genes evolve rapidly and differ between mouse and human. The data and publication deluge related to macrophage biology require the development of new analytical tools and ways of presenting information in an accessible form.