Computational Genomic Epidemiology of Cancer (CoGEC) Training Program

项目摘要/摘要 进行创新的癌症研究需要具有不同背景的科学家团队的投入， 包括分子生物学、肿瘤学、医学、流行病学、生物统计学、基因组学/遗传学、 生物信息学、计算机科学和人工智能。受过跨学科培训的研究人员 这些领域对这样的团队来说非常有价值，因为它们可以作为综合工作的渠道 完成一些最有前途和前瞻性的癌症研究所必需的。由于 然而，这些领域内的培训具有排他性，调查人员的机会有限 获取连接这些学科的知识。为了帮助解决这个问题，我们在此建议 继续这个T32项目，提供计算基因组流行病学的博士后培训 Case综合癌症中心的癌症研究中心(CoGEC)。CoGEC培训计划定义了一种新的、 跨学科领域的培训，涉及癌症研究、流行病学、生物统计学、遗传学、 和计算机科学。该计划的结构由三个关键要求定义。首先，所有受训人员将 有机会选修一门由五门课程组成的专业核心课程，以填补之前 如有必要，进行培训。其次，受训者将进行额外的教学经验选择，以 补充他们的教育和研究背景。第三，所有学员将在以下时间获得研究经验 与多位导师合作开展高水平的癌症基因组流行病学计算项目。AS 作为这一研究经验的延伸，每个受训人员将被要求撰写并为NIH拨款辩护 求婚。在这个项目中接受培训的癌症研究人员将拥有破译 由疾病的遗传和环境风险因素组成的复杂途径。在这样做的时候，他们的知识 这些发现将转化为对癌症的理解、预防和治疗。

PROJECT SUMMARY/ABSTRACT Undertaking innovative cancer research requires input from teams of scientists with a mixture of backgrounds, including molecular biology, oncology, medicine, epidemiology, biostatistics, genomics/genetics, bioinformatics, computer science and artificial intelligence. Researchers with interdisciplinary training across these fields are extremely valuable to such teams, as they can act as conduits for the integrated work necessary to accomplish some of the most promising and forward-looking cancer research. Due to the exclusive nature of training within these fields, however, there are limited opportunities for investigators to obtain the knowledge that bridges these disciplines. To help remedy this problem, we propose here the continuation of this T32 program to provide postdoctoral training in the Computational Genomic Epidemiology of Cancer (CoGEC) at the Case Comprehensive Cancer Center. The CoGEC training program defines a novel, transdisciplinary area of training at the intersection of cancer research, epidemiology, biostatistics, genetics, and computer science. The program’s structure is defined by three key requirements. First, all trainees will have the opportunity to take a specialized core curriculum of five courses to fill in the gaps of their previous training if necessary. Second, the trainees will undertake additional didactic experiences selected to complement their educational and research background. Third, all trainees will obtain research experience by collaborating with multiple mentors on high-level computational genomic epidemiology of cancer projects. As an extension of this research experience, each trainee will be required to write and defend an NIH grant proposal. Cancer researchers obtaining training in this program will have the skills vital to deciphering the complex pathways comprising genetic and environmental risk factors for disease. In doing so, their knowledge and findings will be translated into improved cancer understanding, prevention and treatment.