Two trends are driving innovation and discovery in biological sciences: technologies that allow holistic surveys of genes, proteins, and metabolites and the growing realization that analysis and interpretation of the resulting requires an understanding of the complex factors that mediate the link between genotype and phenotype. The growing body of biological and biomedical information, driven by an exponential drop in the cost of generating genomic data, provides an outstanding opportunity for leveraging what we already â€œknowâ€ in a systematic way to understand the problems that we are studying, including the processes that drive the development of disease phenotypes. Our group uses a variety of bioinformatics and computational approaches, biostatistical analyses, and fundamental laboratory investigation to explore fundamental questions about the nature of human disease. Our approach is based on using high-throughput assays and applying "systems" methods integrate diverse datatypes, including the genome sequence, its annotation, genetic information, phenotype, and the vast body of knowledge captured in the literature. Our goal is not only to develop our own insight into these processes, but to instantiate our methods in tools, protocols, and databases to the broader community that will accelerate research beyond our own.