A Computational Biology and Predictive Health Genomics Training Program at GT

GT 的计算生物学和预测健康基因组学培训项目

• 批准号: 9285807
• 负责人: GREGORY C GIBSON
• 金额: $ 18.64万
• 依托单位: GEORGIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9285807
• 关键词: Computational Biology; Genomics; Health; Training Programs

DESCRIPTION (provided by applicant): A Computational Biology and Biomedical Genomics Training Program at The Georgia Institute of Technology This T32 Proposal would establish a Ruth Kirschstein Institutional Training Program in Bioinformatics and Computational Biology at Georgia Tech. It builds on the solid foundation of over a decade of graduate training in Bioinformatics, as well as existing strengths in systems biology and computational modeling allied to genomics through one of the nation's leading Biomedical Engineering departments. Funding is requested to support two new Ph.D. students per year for five years, providing stability and supporting innovation during the crucial second and third years in the program when they are transitioning from course work to independent research. Five key features of the program are (i) the establishment of a computational genomics training program for the south-eastern United States, (ii) a broad base for recruitment across Biology, Bio-Engineering, and Health Systems statistical research, (iii) a highly interdisciplinary series of courses integrating bioinformatics, computational genomics, multivariate statistics, quantitative genetics, molecular evolution, and systems modeling, (iv) excellence in under- represented minority recruitment and graduation with over 15% of the student body African American or Hispanic, and (v) establishment of one of the first training programs specifically oriented to predictive health genomics, also linked to a long-term vision for Masters-level training of clinical genomicists. The trainees will be selected on a competitive basis from an expected pool of ten candidates per year spread across 23 mentor's research groups. Each year's cohort in the Computational Biology and Biomedical Genomics program will take an introductory two-semester ground course and core classes in computational theory and methods, then specialize in bioinformatics, systems biology, or predictive health. Students will graduate with a balance of knowledge across the fundamentals of computational genetics, molecular/cell biology and evolutionary theory, while performing research that in many cases is oriented toward translational research in bioengineering and health care innovation.

描述（由申请人提供）：佐治亚理工学院的计算生物学和生物医学基因组学培训计划 该 T32 提案将在佐治亚理工学院建立生物信息学和计算生物学 Ruth Kirschstein 机构培训计划。它建立在十多年来生物信息学研究生培训的坚实基础上，以及通过美国领先的生物医学工程系之一在系统生物学和与基因组学相关的计算模型方面的现有优势。请求资金支持两名新博士。五年内每年为学生提供稳定性，并在该项目关键的第二年和第三年从课程工作过渡到独立研究期间提供稳定性和支持创新。该计划的五个关键特点是（i）为美国东南部建立计算基因组学培训计划，（ii）为生物学、生物工程和卫生系统统计研究领域的招募提供广泛的基础，（iii）高度跨学科的系列课程，整合了 生物信息学、计算基因组学、多元统计、定量遗传学、分子进化和系统建模，(iv) 在代表性不足的少数族裔招生和毕业方面表现出色，其中超过 15% 的学生为非洲裔美国人或西班牙裔，以及 (v) 建立第一个专门针对预测健康基因组学的培训项目，也与临床硕士水平培训的长期愿景相关 基因组学家。这 每年预计将有 10 名候选人，分布在 23 个导师的研究小组中，通过竞争的方式选出受训者。每年计算生物学和生物医学基因组学项目的学生将学习两个学期的入门基础课程和计算理论和方法的核心课程，然后专注于生物信息学、系统生物学或预测健康。学生毕业时将掌握计算遗传学、分子/细胞生物学和进化论基础知识的平衡知识，同时开展在许多情况下面向生物工程和医疗保健创新领域的转化研究的研究。