Training Program for Quantitative Population Sciences in Cancer

癌症定量人口科学培训计划

• 批准号: 10675063
• 负责人: MARGARET Rita KARAGAS
• 金额: $ 25.95万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-07 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10675063
• 关键词: Malignant Neoplasms; Population Sciences; Training Programs

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.

项目摘要/摘要 现代生物医学研究依赖于新方法来促进我们对复杂和复杂的理解 多方面的疾病，具有越来越多的公共卫生意义，例如癌症。新兴技术启用 人群科学家以从未想象到的规模生成数据（即，通过整个基因组阵列 扫描）。这不仅需要在经典学科中训练下一代科学家 参与人类恶性肿瘤的研究，但要在完善学科中进行交叉训练以允许他们 揭露他们的科学发现。因此，我们建议继续一个非常成功的博士后 在生物信息学领域结合专业研究知识和方法的计划， 生物统计学和流行病学。这个新颖的计划，名为“定量人口的培训计划 癌症科学的结构是完成现有的癌症研究和教育资源 Geisel医学院和NORRIS棉花癌中心（NCCC），NCI指定 达特茅斯（Dartmouth）和达特茅斯（Dartmouth）盖塞尔医学院的全面癌症中心分支机构 希区柯克医疗中心（DHMC）。我们的培训工作将继续由调查员领导 在生物信息学，生物统计学和流行病学领域的完全专业知识 生物医学数据科学，流行病学和分子和系统生物学部门。我们将 利用这些学科的达特茅斯有才华的干部教师，他们可以提供专家指导，并 可以提供有关大量人群科学数据的研究和中心赠款的多功能投资组合， 生物样品和核心研究设施。为了实现我们的目标，我们建议交叉培训八 流行病学，生物信息学或生物统计学的学期学士为2至3年。学员会 与来自两个焦点学科的主要和继发性心理配对，并完全交叉 纪律课程具有定量生物医学科学的可选MS学位。在第二年 该计划的三个，学员将集中精力进行修改研究活动，准备一个模拟 NIH赠款申请，并参加专业手稿的准备 研讨会和科学会议以及可选的研究实质性。计划负责人，咨询 与咨询委员会一起，将选择受训者，监控其进度并向 确保提供必要的教学和研究经验，以产生知识渊博的知识渊博 人口科学中跨学科癌症研究未来的研究者。最终目标 该培训计划是通过增强现有的癌症研究人员来加速癌症研究 凭借满足人群翻译癌症研究的当前和未来挑战的技能 科学。

项目成果

A Novel Pathway-Based Approach Improves Lung Cancer Risk Prediction Using Germline Genetic Variations.

• DOI: 10.1158/1055-9965.epi-15-1318
• 发表时间: 2016-08
• 期刊: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
• 作者: Qian DC;Han Y;Byun J;Shin HR;Hung RJ;McLaughlin JR;Landi MT;Seminara D;Amos CI
• 通讯作者: Amos CI

Robustness, evolvability, and the logic of genetic regulation.

鲁棒性、进化性和遗传调控的逻辑。

• DOI: 10.1162/artl_a_00099
• 发表时间: 2014
• 期刊: Artificial life
• 影响因子: 2.6
• 作者: Payne,JoshuaL;Moore,JasonH;Wagner,Andreas
• 通讯作者: Wagner,Andreas

Testing domain knowledge and risk of bias of a large-scale general artificial intelligence model in mental health.

• DOI: 10.1177/20552076231170499
• 发表时间: 2023-01
• 期刊: DIGITAL HEALTH
• 影响因子: 3.9
• 作者: Heinz, Michael V.;Bhattacharya, Sukanya;Trudeau, Brianna;Quist, Rachel;Song, Seo Ho;Lee, Camilla M.;Jacobson, Nicholas C.
• 通讯作者: Jacobson, Nicholas C.

MicroRNA molecular profiling from matched tumor and bio-fluids in bladder cancer.

• DOI: 10.1186/s12943-015-0466-2
• 发表时间: 2015-11-14
• 期刊: Molecular cancer
• 影响因子: 37.3
• 作者: Armstrong DA;Green BB;Seigne JD;Schned AR;Marsit CJ
• 通讯作者: Marsit CJ

Association of adiposity, telomere length and mortality: data from the NHANES 1999-2002.

• DOI: 10.1038/ijo.2017.202
• 发表时间: 2018-03
• 期刊: International journal of obesity (2005)
• 作者: Batsis JA;Mackenzie TA;Vasquez E;Germain CM;Emeny RT;Rippberger P;Lopez-Jimenez F;Bartels SJ
• 通讯作者: Bartels SJ