The prevalence and morbidity of asthma, a chronic inflammatory airway disease, is increasing. Animal models provide a meaningful but limited view of the mechanisms of asthma in humans. A systems-level view of asthma that integrates multiple levels of molecular and functional information is needed. For this, we compiled a gene expression compendium from five publicly available mouse microarray datasets and a gene knowledge base of 4,305 gene annotation sets. Using this collection we generated a high-level map of the functional themes that characterize animal models of asthma, dominated by innate and adaptive immune response. We used Module Networks analysis to identify co-regulated gene modules. The resulting modules reflect four distinct responses to treatment, including early response, general induction, repression, and IL-13-dependent response. One module with a persistent induction in response to treatment is mainly composed of genes with suggested roles in asthma, suggesting a similar role for other module members. Analysis of IL-13-dependent response using protein interaction networks highlights a role for TGF-beta1 as a key regulator of asthma. Our analysis demonstrates the discovery potential of systems-level approaches and provides a framework for applying such approaches to asthma.