Training Program for Quantitative Population Sciences in Cancer

项目摘要/摘要 现代生物医学研究依赖于新的方法来促进我们对复杂和 癌症等对公共卫生日益重要的多方面疾病。新兴技术使 人口科学家将以前所未有的规模(即通过全基因组阵列)生成数据 扫描)。因此，迫切需要的不仅是培养下一代经典学科的科学家。 参与人类恶性肿瘤的研究，但在互补的学科中交叉培训他们，以使他们 将他们的科学发现公之于众。因此，我们建议继续一个非常成功的博士后 该计划结合了生物信息学领域的专门研究知识和方法， 生物统计学和流行病学。这是一项名为“数量人口培训计划”的新计划 癌症科学》，旨在补充现有的癌症研究和教育资源，网址为 盖泽尔医学院和诺里斯棉花癌症中心(NCCC)，NCI指定的 达特茅斯和达特茅斯的盖泽尔医学院附属的综合癌症中心 希区柯克医疗中心(DHMC)。我们的培训工作将继续由调查人员领导， 生物信息学、生物统计学和流行病学领域的补充专门知识，主要是在 生物医学数据科学系、流行病学系和分子与系统生物学系。我们会 利用达特茅斯大学在这些学科方面的有才华的干部教师，他们可以提供专家指导，以及 多种多样的研究和中心拨款组合，可以提供对丰富的人口科学数据的访问， 生物样本和核心研究设施。为了实现我们的目标，我们建议交叉培训八个 流行病学、生物信息学或生物统计学方面的博士后培训生，为期2至3年。实习生将 与两个重点学科的主要和次要导师配对，并完成交叉- 具有定量生物医学科学硕士学位的选修课。在两年内和 在三期节目中，学员将集中精力进行辅导研讨活动，准备模拟 NIH拨款申请，并参与专业手稿的准备，在 研讨会和科学会议，以及可选的外部研究奖学金。项目负责人，在协商中 通过一个咨询委员会，将挑选受训人员，监测他们的进展，并提供建议，以 确保提供必要的教学和研究经验，以培养高度知识化的人才 人口科学中未来跨学科癌症研究的研究人员。的最终目标是 该培训计划旨在通过加强现有的癌症研究人员库来加速癌症研究 具备应对人口中转化性癌症研究当前和未来挑战的技能 科学。

PROJECT SUMMARY/ABSTRACT Modern biomedical research relies on new approaches to advance our understanding of complex and multifaceted illnesses of growing public health significance such as cancer. Emerging technologies 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 allow them to bring their scientific discoveries to light. Therefore, we propose to continue a highly successful 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,” is structured to complement the existing resources for cancer research and education at the Geisel School of Medicine and the Norris Cotton Cancer Center (NCCC), an NCI designated Comprehensive Cancer Center affiliated with the Geisel School of Medicine at Dartmouth and Dartmouth Hitchcock Medical Center (DHMC). Our training efforts will continue to be led by investigators with complementary expertise in the fields of bioinformatics, biostatistics and epidemiology primarily within the Departments of Biomedical Data Science, Epidemiology and Molecular and Systems Biology. We will capitalize on Dartmouth’s talented cadre faculty in these disciplines who can offer expert mentorship, and a versatile portfolio of research and center grants that can supply access to a wealth of population science data, biologic samples and core research facilities. To accomplish our objectives, we propose to cross-train eight postdoctoral trainees in epidemiology, bioinformatics or biostatistics for a period of 2 to 3 years. Trainees will be paired with a primary and secondary mentor from two of the focus disciplines and complete cross- disciplinary coursework with an optional MS degree in Quantitative Biomedical Sciences. 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, presentations at symposia and scientific conferences and an optional research externship. Program leaders, in consultation with an Advisory Committee, 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 to meet the present and future challenges in translational cancer research in the population sciences.