Computational Genomic Epidemiology of Cancer (CoGEC) Training Program

癌症计算基因组流行病学 (CoGEC) 培训计划

• 批准号: 10215403
• 负责人: Rong Xu
• 金额: $ 30.23万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10215403
• 关键词: Training Programs; cancer epidemiology; genomic epidemiology

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, and computer science. 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 Case Comprehensive Cancer Center. This 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 take a specialized core curriculum of five courses that cover the individual disciplines as well as their intersections . 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 a mock NIH 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, they will ultimately be able to provide clinicians and their patients with invaluable information for the prevention and treatment of cancer.

摘要 进行创新的癌症研究需要来自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， 生物信息学和计算机科学。在这些领域受过跨学科培训的研究人员 这对这些团队来说是非常有价值的，因为他们可以作为完成必要的综合工作的管道， 一些最有前途和前瞻性的癌症研究。由于内部培训的排他性， 然而，在这些领域，研究人员获得连接这些领域的知识的机会有限。 这些纪律。为了帮助解决这个问题，我们在这里建议继续这个T32计划， 在Case提供癌症计算基因组流行病学（CoGEC）的博士后培训 综合癌症中心。该计划定义了一个新颖的，跨学科的培训领域， 癌症研究、流行病学、生物统计学、遗传学和计算机科学的交叉。该计划的 结构由三个关键要求定义。首先，所有学员将参加五门专业核心课程， 涵盖各个学科及其交叉点的课程。第二，学员将承担 选择额外的教学经验，以补充他们的教育和研究背景。三是各 学员将通过与多位导师合作进行高级计算， 癌症基因组流行病学项目。作为这项研究经验的延伸，每个学员将 写一份模拟的NIH提案并为之辩护癌症研究人员获得培训，在这一计划将 具有破译包括遗传和环境风险因素在内的复杂途径的关键技能， 疾病通过这样做，他们最终将能够为临床医生和他们的病人提供宝贵的 预防和治疗癌症的信息。