Gene expression microarrays can estimate the prevalence of mRNA for thousands of genes in a small sample of cells or tissue. Organ transplant researchers are increasingly using microarrays to identify specific patterns of gene expression that predict and characterize acute and chronic rejection, and to improve our understanding of the mechanisms underlying organ allograft dysfunction. We used microarrays to assess gene expression in bronchoalveolar lavage cell samples from lung transplant recipients with and without acute rejection on simultaneous lung biopsies. These studies showed increased expression during acute rejection of genes involved in inflammation, apoptosis, and T-cell activation and proliferation. We also studied gene expression during the evolution of airway obliteration in a murine heterotopic tracheal transplant model of chronic rejection. These studies demonstrated specific patterns of gene expression at defined time points after transplantation in allografts, whereas gene expression in isografts reverted back to that of native tracheas within 2 wk after transplantation. These studies demonstrate the potential power of microarrays to identify biomarkers of acute and chronic lung rejection. The application of new genetic, genomic, and proteomic technologies is in its infancy, and the microarray-based studies described here are clearly only the beginning of their application to lung transplantation. The massive amount of data generated per tissue or cell sample has spawned an outpouring of invention in the bioinformatics field, which is developing methodologies to turn data into meaningful and reproducible clinical and mechanistic inferences.