Computational Genomic Epidemiology of Cancer (CoGEC) Training Program

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、 生物信息学和计算机科学。在这些领域接受过跨学科培训的研究人员 对这样的团队来说非常有价值，因为他们可以作为完成必要的综合工作的渠道 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，这些领域的调查人员获得知识的机会有限， 这些学科。为了帮助解决此问题，我们在此建议继续此T32计划以 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学科。该计划的 结构由三个关键要求定义。首先，所有受训人员将选修五门专业核心课程。 涵盖各个学科及其交叉点的课程。第二，受训人员将承担 选择额外的教学经验来补充他们的教育和研究背景。第三，所有 学员将通过与多位导师在高级计算方面的合作获得研究经验 癌症基因组流行病学项目。作为这一研究经验的延伸，每个受训人员都将 被要求撰写和辩护一份模拟的NIH提案。接受该计划培训的癌症研究人员将 拥有对破译由遗传和环境风险因素组成的复杂途径至关重要的技能 疾病。通过这样做，他们最终将能够为临床医生和他们的患者提供无价的 关于预防和治疗癌症的信息。

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.