The integration of molecular, genomic, and clinical medicine in the post-genome era provides the promise of novel information on genetic variation and pathophysiologic cascades. The current challenge is to translate these discoveries rapidly into viable biomarkers that identify susceptible populations and into the development of precisely targeted therapies. In this article, we describe the application of comparative genomics, microarray platforms, genetic epidemiology, statistical genetics, and bioinformatic approaches within examples of complex pulmonary pathobiology. Our search for candidate genes, which are gene variations that drive susceptibility to and severity of enigmatic acute and chronic lung disorders, provides a logical framework to understand better the evolution of genomic medicine. The dissection of the genetic basis of complex diseases and the development of highly individualized therapies remain lofty but achievable goals.Increased morbidity and mortality from acute and chronic pulmonary disorders represent sources of enormous health-care expenditures 1 -6 and mandate better understanding of lung pathobiology. The unraveling of the genetic basis of complex pulmonary diseases such as asthma, emphysema, acute lung inury (ALI), and pulmonary hypertension (PH) provides an opportunity to improve the delivery of targeted therapies that reduce the suffering of patients with these disorders. The challenge, however, historically has been daunting as traditional methods of genetic research, with limited technologies, could only consider the study of individual genes. The complexity of genomic structure and function, disease heterogeneity, the influence of the environment on disease development and progression, and epigenetic mechanisms also contribute to the challenge of mastering the genetic underpinnings of complex lung diseases. Fortunately, in the era after the completion of the Human Genome Project, the availability of multiple high-throughput genomic and genetic technologies now allows elucidation of complex pathophysiology cascades produced by the carefully orchestrated spatial and temporal regulation of tens to hundreds of genes and proteins. In this article, we provide examples of the application of these emerging genomic tools as we integrate genomic knowledge with clinical medicine. We discuss the use of several novel and potentially useful approaches: whole genome linkage analysis scans, conventional candidate gene and single nucleotide polymorphism (SNP)-based approaches, and preclinical animal models of human disease. Ultimately, the promise of the post-genome era is that the increased application of genomic technologies and innovative bioinformatics will translate clinical-based discovery into the personalized medicine experience with the development and identification of novel biomarkers, diagnostic strategies, prognostic indicators, and targets for therapeutic intervention.