PROJECT SUMMARY There is a broad consensus that obesity, diabetes, and its many complications represent one of the major public health crises of the 21st century in the United States and globally. Biomedical research efforts aimed at characterization of the etiology, diagnoses, prognosis, and outcomes of diabetes has increasingly generated large amounts of complex data in many scientific fields including structural biology, informatics, metabolomics, whole genome sequencing, proteomics, phenotypic datasets, electronic health records, and public health datasets. Computational and mathematical methods in bioinformatics, clinical informatics, data visualization, and mathematical modeling are needed to analyze and interpret the plethora of data to improve the lives of people with diabetes. With unique resources such as the Utah Population Database, the Utah Genome Project, the Department of Biomedical Informatics, and Utah's Diabetes and Metabolism Center, the University of Utah has an exceptional training environment and has seen many dual-mentored trainees establish independent research careers. In this application we propose to formally establish an NIDDK Interdisciplinary Training Program in Computational Approaches to Diabetes and Metabolism Research at the University of Utah under the leadership of Wendy Chapman, PhD, Chair of the Department of Biomedical Informatics, and Simon Fisher, MD, PhD, Chief of the Division of Endocrinology and Co-Director of the Diabetes and Metabolism Center at the University of Utah. The proposed multidisciplinary training program spans 18 departments at the University. The goal of this interdisciplinary program is to prepare predoctoral and postdoctoral trainees to be leaders in computational and mathematical methods and engage them in the analysis of large data sets involving complex biological problems in diabetes, obesity, and metabolism. Each trainee will participate in a two-year training program that includes a research project with a multidisciplinary mentoring committee, didactic coursework, and professional development opportunities. Each trainee will receive dual mentorship from both a computational and a biological mentor. The mentoring committees, tailored to each trainee's research interests, will draw from a mentor pool of 55 MD and PhD investigators (26 computational/mathematic mentors and 29 diabetes/metabolism mentors). The training program will be overseen by an executive committee comprising the two Principal Investigators and five Co-Directors, all of whom are investigators with strong track records of uncompromising commitment to mentoring trainees. We are requesting support for five trainee positions (three predoctoral and two postdoctoral) to train a total of 12 scientists over 5 years. With this unique interdisciplinary training experience, we expect our trainees to become world leaders in the application of bioinformatics to diabetes, obesity, and metabolism research.

PROJECT NARRATIVE To accelerate the pace of diabetes research, there is a pressing need to train computational scientists the biological basis of diabetes and related metabolic disorders. This proposal will serve to create a training program that will train both predoctoral and postdoctoral trainees in the computational and mathematical sciences and in the biological basis of diabetes and obesity. These bioinformatics scientist trainees will gain the expertise and leadership skills to apply computational methods to complex biological questions that will ultimately impact the prevention, treatment, and outcomes of people with diabetes and related metabolic diseases.