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: 8473373
• 负责人: GREGORY C GIBSON
• 金额: $ 18.05万
• 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/8473373
• 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）：该T32提案将在佐治亚理工学院建立Ruth Kirschstein生物信息学和计算生物学机构培训计划。该计划建立在十多年生物信息学研究生培训的坚实基础之上。以及在系统生物学和计算建模方面的现有优势，通过全国领先的生物医学工程系之一与基因组学相结合。基金要求每年支持两名新的博士研究生，为期五年，在项目的关键的第二和第三年，当他们从课程工作过渡到独立研究时，提供稳定和支持创新。该计划的五个主要特点是：(i)为美国东南部建立一个计算基因组学培训计划，（ii）在生物学、生物工程和卫生系统统计研究方面的广泛招聘基础，（iii）高度跨学科的一系列课程整合