Mitochondria are tiny organelles found in nearly all cells, serving as the center stage for ATP production, ion homeostasis, and apoptosis. Their composition, density, and coupling efficiency are dynamic properties, varying across cell types and adapting to changes in energetic status during growth and differentiation. Recent studies have implicated mitochondrial dysfunction in a variety of human diseases, including diabetes, cancer, neurodegeneration, and aging. My group is broadly interested in characterizing the structure and dynamic properties of the biological networks underlying mitochondrial function, linking variation in these parameters to genetic variation, and exploiting the network properties of the organelle to design therapies for human disease. To achieve these goals, we are using experimental approaches that combine classic biochemistry with the new tools of genomics. We make chemical and genetic perturbations in cellular systems that can be systematically profiled using microarrays and tandem mass spectrometry. We are also developing computational and statistical techniques to integrate these vast datasets to link biological networks with measures of biochemical function. In this manner we hope to construct predictive models of mitochondrial remodeling that can then be validated with additional rounds of perturbation. Simultaneously, we are working in close collaboration with clinicians and geneticists to apply genome-scale profiling technologies to study human metabolic disorders. Currently our clinical studies are focused on mitochondrial respiratory chain diseases. By integrating the results from our in vitro experiments with those from our human studies, we hope to uncover the biological networks that are operative in human disease.