Interdisciplinary Research Training in Biostatistics

生物统计学跨学科研究培训

• 批准号: 7089917
• 负责人: LEE-JEN WEI
• 金额: $ 18.17万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7089917
• 关键词: Interdisciplinary; Research; Training; Biostatistics

DESCRIPTION (provided by applicant): This training program is designed to develop a cadre of young biostatistical scientists to become leaders in integrative and team approaches to understanding biological science in the public health arena. Susceptibility to many complex diseases can be governed by the interactions between modifier genes and environmental factors. In the post-genomic era we are beginning to comprehend and compile the breadth of genetic variation within the human population. Refined use of this information requires the development of advanced methods of biostatistical analyses. In addition, to make significant progress in disease prevention, a hallmark of public health, there is a pressing need to translate advances in basic science into programs and policies focused on preventing common and costly chronic diseases. Only by integrating emerging scientific information into the design of clinical and public health interventions can we fully extract the value of these advances for public health. The established tools of probability and statistical inference remain critical to the success in the training of this new generation of biostatisticians, but in addition they must be conversant with the biological basis and data structures encountered in studies that incorporate genetic information, data produced by expression arrays, and that seek to establish connections between data collected in different approaches to the study of biological systems. They will also need a strong grounding in the information sciences preparing them to utilize computationally-intensive methods such as Markov Chain Monte Carlo procedures and semi-parametric models. This training program combines those elements with experiential training in laboratory science and computational biology and directed interdisciplinary research that will prepare graduates to meet this challenge.

描述（由申请人提供）：该培训计划旨在培养一批年轻的生物统计学科学家，使他们成为在公共卫生领域理解生物科学的综合和团队方法的领导者。对许多复杂疾病的易感性可以通过修饰基因和环境因素之间的相互作用来控制。在后基因组时代，我们开始理解和整理人类遗传变异的广度。对这些信息的精细利用需要开发先进的生物统计分析方法。此外，为了在作为公共卫生标志的疾病预防方面取得重大进展，迫切需要将基础科学的进步转化为重点预防常见且昂贵的慢性疾病的计划和政策。只有将新兴的科学信息融入临床和公共卫生干预措施的设计中，我们才能充分发挥这些进步对公共卫生的价值。既定的概率和统计推断工具对于新一代生物统计学家的培训成功仍然至关重要，但此外，它们还必须熟悉在研究中遇到的生物学基础和数据结构，这些研究结合了遗传信息、表达阵列产生的数据，并寻求在生物系统研究的不同方法中收集的数据之间建立联系。他们还需要在信息科学方面有坚实的基础，以便他们能够利用计算密集型方法，例如马尔可夫链蒙特卡罗程序和半参数模型。该培训计划将这些要素与实验室科学和计算生物学的体验式培训以及定向跨学科研究相结合，帮助毕业生做好应对这一挑战的准备。