Training Program for Quantitative Population Sciences in Cancer

描述（由申请人提供）：现代生物医学研究依赖于多学科和跨学科的方法来推进我们对复杂和多方面的疾病的理解，这些疾病对公众健康的影响越来越大，如癌症。新兴技术将使人口科学家能够以前所未有的规模生成数据（即通过全基因组阵列扫描）。因此，迫切需要不仅在涉及人类恶性肿瘤研究的经典学科方面培训下一代科学家，而且在互补学科方面对他们进行交叉培训，使他们能够将自己的科学发现揭示出来。因此，我们建议建立一个结合生物信息学、生物统计学和流行病学领域的专业研究知识和方法的博士后项目。这个新颖的项目名为“癌症定量人口科学培训项目”，其结构将补充达特茅斯医学院（DMS）现有的癌症研究和教育资源，并将与诺里斯棉花癌症中心（NCCC）的使命保持一致，NCCC是一个NCI指定的综合癌症中心，隶属于达特茅斯医学院和达特茅斯希区柯克医疗中心（DHMC）。培训工作将由遗传学、社区和家庭医学系/生物统计和流行病学科内生物信息学、生物统计和流行病学领域的既定调查人员领导。为了实现我们的目标，我们建议交叉培养6名流行病学，生物信息学或生物统计学博士后，为期2至3年。学员将在项目的第一年完成跨学科课程，并将与来自两个重点学科的主要和次要导师配对。在项目的第二年和第三年，受训者将专注于指导研究活动的进行，准备模拟NIH拨款申请，参与专业手稿的准备工作，并在研讨会和科学会议上发表演讲。一个由拟议学科的领导和导师组成的咨询委员会将选择受训者，监测他们的进展，并提出建议，以确保提供必要的教学和研究经验，为人口科学跨学科癌症研究的未来培养知识渊博的调查人员。培训计划的最终目标是通过提高现有的癌症研究人员的技能来加速癌症研究，以满足人口科学中转化癌症研究的当前和未来需求。

DESCRIPTION (provided by applicant): Modern biomedical research relies on both multidisciplinary and interdisciplinary approaches to advance our understanding of complex and multifaceted illnesses of growing public health significance such as cancer. Emerging technologies will enable population scientists to generate data on a scale never before imaginable (i.e., through whole genome array scans). Thus, there is a critical need to not only train the next generation of scientists in the classic disciplines involved in studies of human malignancies, but to cross-train them in complementary disciplines to enable them to bring their scientific discoveries to light. Therefore, we propose a postdoctoral program that combines specialized research knowledge and methodologies in the fields of bioinformatics, biostatistics and epidemiology. This novel program, entitled "Training Program for Quantitative Population Sciences in Cancer," will be structured to complement the existing resources for cancer research and education at Dartmouth Medical School (DMS) and will be aligned with the mission of the Norris Cotton Cancer Center (NCCC), an NCI designated Comprehensive Cancer Center affiliated with Dartmouth Medical School and Dartmouth Hitchcock Medical Center (DHMC). The training efforts will be led by established investigators in the fields of bioinformatics, biostatistics and epidemiology within the Departments of Genetics and Community and Family Medicine/Section of Biostatistics and Epidemiology. To accomplish our objectives, we propose to cross-train six postdoctoral trainees in epidemiology, bioinformatics or biostatistics for a period of 2 to 3 years. Trainees will complete cross-disciplinary coursework in the first year of the program and will be paired with a primary and secondary mentor from two of the focus disciplines. In years two and three of the program, trainees will concentrate on the conduct of mentored research activities, prepare a mock NIH grant application and participate in the preparation of professional manuscripts and presentations at seminars and scientific conferences. An Advisory Committee composed of the leaders and mentors of the proposed disciplines will select trainees, monitor their progress and provide recommendations to ensure that the necessary didactic and research experiences are provided to produce highly knowledgeable investigators for the future of interdisciplinary cancer research in the population sciences. The ultimate goal of the training program is to accelerate cancer research by enhancing the existing pool of cancer researchers with the skills needed to meet the present and future needs in translational cancer research in the population sciences.