University of Utah Interdisciplinary Training Program in Computational Approaches to Diabetes and Metabolism Research

项目总结 人们普遍认为，肥胖、糖尿病及其许多并发症是主要的 21世纪美国和全球的公共卫生危机。生物医学研究的目标是 对糖尿病的病因、诊断、预后和结果的描述越来越多 结构生物学、信息学、代谢组学等多个科学领域的大量复杂数据， 全基因组测序、蛋白质组学、表型数据集、电子健康记录和公共卫生 数据集。生物信息学、临床信息学、数据可视化、 需要数学建模来分析和解释过多的数据，以改善人们的生活 糖尿病患者。拥有独特的资源，如犹他州人口数据库，美国犹他州基因组计划， 犹他州大学生物医学信息学系和犹他州糖尿病与代谢中心 有一个特殊的培训环境，并看到许多双导师学员建立了独立的 从事研究工作。在本申请中，我们建议正式建立NIDDK跨学科培训 犹他大学糖尿病和代谢研究计算方法项目 生物医学信息学系主任温迪·查普曼博士和西蒙的领导 费舍尔，医学博士，内分泌科主任兼糖尿病和新陈代谢联席主任 在犹他大学的研究中心。拟议的多学科培训计划横跨18个部门 大学。这个跨学科项目的目标是培养博士后和博士后实习生成为 在计算和数学方法方面处于领先地位，并让他们参与大数据集的分析 涉及糖尿病、肥胖症和新陈代谢等复杂的生物学问题。每个实习生将参加一个 为期两年的培训计划，包括一个与多学科指导委员会一起的研究项目， 讲授课程，以及职业发展机会。每位学员将得到双重指导。 从计算导师和生物学导师那里。指导委员会，为每个学员量身定做 研究兴趣，将从55名医学博士和博士研究人员(26名计算/数学)导师库中挑选 导师和29名糖尿病/新陈代谢导师)。培训计划将由一名高管监督 由两名首席调查员和五名联席董事组成的委员会，他们都是调查人员 坚定不移地致力于指导学员的良好记录。我们请求为五个人提供支持 实习生职位(三个博士后和两个博士后)，在5年内共培训12名科学家。有了这个 独特的跨学科培训经验，我们期待我们的学员在应用方面成为世界领先者 将生物信息学应用于糖尿病、肥胖症和新陈代谢研究。

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.