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

项目概要 该申请代表了犹他大学 (UofU) 的第一个竞争性续签申请 糖尿病和代谢研究计算方法跨学科培训 T32 项目 （CADMR T32）。该项目对博士前和博士后学员进行计算和计算方面的交叉培训 数学科学以及糖尿病和肥胖的生物学基础。我们的计划学员获得 将计算和数学方法应用于复杂生物的专业知识和领导技能 最终将影响糖尿病患者的预防、治疗和结果的问题 相关代谢性疾病。该培训计划包括指导研究和职业生涯的结合 发展培训、课程作业以及与校园内的教师和学员的广泛互动 超越。拥有基因组医学中心、犹他州人口数据库、 犹他州基因组计划、生物医学信息学系以及糖尿病和代谢研究 中心，犹他大学拥有优越的培训环境，并见证了许多双导师 学员建立独立的研究生涯。 CADMR T32 将由两名 PI 领导，他们 计算（Karen Eilbeck 博士）和糖尿病专业知识（Simon Fisher 博士）。拟议的多学科 培训计划涵盖大学 13 个系。这个跨学科计划的目标是 培养博士前和博士后学员成为计算和数学方法的领导者 让他们参与涉及糖尿病、肥胖症等复杂生物学问题的大型数据集的分析 新陈代谢。每位学员将参加为期两年的培训计划，其中包括一个研究项目 多学科指导委员会、教学课程和专业发展机会。每个 学员将获得计算导师和生物导师的双重指导。辅导 根据每位学员的研究兴趣量身定制的委员会将从 38 名医学博士和博士组成的导师库中选拔 研究人员（15 名计算/数学导师和 23 名糖尿病/代谢导师）。培训内容 该计划将由指导委员会监督，该委员会由两名首席研究员和四名 委员会成员都是调查员，有着坚定不移的承诺记录 指导学员。我们请求支持五个实习生职位（三个博士前和两个 博士后）在5年内总共培养15名科学家。凭借这种独特的跨学科培训经验， 我们期望我们的学员成为将生物信息学应用于糖尿病、肥胖症和糖尿病等领域的世界领导者 代谢研究。

PROJECT SUMMARY This application represents the first competitive renewal application for the University of Utah’s (UofU) Interdisciplinary Training T32 Program in Computational Approaches to Diabetes and Metabolism Research (CADMR T32). This program cross-trains both predoctoral and postdoctoral trainees in the computational and mathematical sciences and in the biological basis of diabetes and obesity. Our program trainees gain the expertise and leadership skills to apply computational and mathematical methods to complex biological questions that will ultimately impact the prevention, treatment, and outcomes of people with diabetes and related metabolic diseases. This training program consists of a combination of mentored research and career development training, coursework, and extensive interactions with faculty and trainees across campus and beyond. With unique resources such as the Center for Genomic Medicine, the Utah Population Database, the Utah Genome Project, the Department of Biomedical Informatics, and the Diabetes and Metabolism Research Center, the University of Utah has an exceptional training environment and has seen many dual-mentored trainees establish independent research careers. The CADMR T32 will be led by two PIs who have computational (Dr. Karen Eilbeck) and diabetes expertise (Dr. Simon Fisher). The proposed multidisciplinary training program spans 13 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 38 MD and PhD investigators (15 computational/mathematic mentors and 23 diabetes/metabolism mentors). The training program will be overseen by a Steering Committee comprising the two Principal Investigators and four committee members, 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 15 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.