My lab's research program combines computational and experimental approaches to map and functionally characterize gene regulatory networks. Our aim is to develop data-driven approaches to “reverse engineer” the regulatory networks that control immune responses in host defense against pathogens and in chronic inflammatory diseases. A comprehensive understanding of these networks is a gateway to being able to predict how the immune system will respond to novel therapies, pathogens, and vaccines. On the computational side, we use integrative machine-learning methods to both identify the genomic regulatory elements that mediate transcriptional control in specific cell types, and to leverage information from genetic epidemiology and from molecular networks to uncover novel molecular regulators of inflammatory responses. On the experimental side, we have been studying the mammalian macrophage (a key constituent of the innate immune system) as both a primary application area and a “test-bed” for integrative methods development. Together with collaborators, we are also employing this systems biology approach in studies of gene regulation in other cell types such as smooth muscle cells and cancer cells.