The Administrative Core for the Nebraska Center for the Prevention of Obesity Diseases through Dietary Molecules (NPOD) will lead, implement, and support the Center's primary activities. These activities are designed to accomplish the NPOD goal to create a nationally recognized center charged with (1) developing and sustaining a critical mass of investigators dedicated to obesity research and (2) leveraging Center discoveries to devise and implement effective strategies for the prevention of obesity-related diseases through the dietary manipulation of nutrient signaling pathways. The Administrative Core will provide the administrative and programmatic leadership and infrastructure necessary to ensure the NPOD functions efficiently and effectively and is responsive to emerging research opportunities. This will include implementing Center-wide activities - including biannual retreats, formal and informal training, and a seminar series - to create a collaborative research environment, promote the Center on a national level, and build a pool of talented doctoral and postdoctoral students in the laboratories of NPOD members. The Administrative Core will coordinate a faculty development plan that includes a research project program and pilot grant program designed to accelerate the transition of talented Project Leaders to independence and support the development of large multi-investigator grants, program projects, and training grants. The Administrative Core also includes Translational Coordinators with expertise in clinical studies and consumer behavior whose involvement will increase the rate and extent of translation of research discoveries into preventing disease. Finally, the Administrative Core will serve as a coordination point between Center members and the Center's Molecular Biology, Bioinformatics and Biostatistics Core (MB^C) services. The Administrative Core will support a research program and Bioinformatics Coordinators in the MB^C to develop innovative tools in nutrient signaling research and provide guidance in experimental design and data analysis.