Core E: Comparative Data Analytics Core

核心 E：比较数据分析核心

• 批准号: 8958642
• 负责人: DAVID B ALLISON
• 金额: $ 8.67万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-15 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8958642
• 关键词: Address; Aging; Animal Model; Basic Science; Biological Process; Biological Sciences; Biology; Biology of Aging; Body Composition; Clinic; Communities; Comparative Biology; Comparative Study; Data; Dependence; Dependency; Development; Event; Face; Frequencies; Hand; Immune; Institute of Medicine (U.S.); Investigation; Investments; Knowledge; Leadership; Left; Longevity; Longitudinal Studies; Mathematics; Measurement; Methods; Modeling; National Research Council; Organism; Outcome; Phylogenetic Analysis; Procedures; Publications; Recording of previous events; Reporting; Reproducibility; Research; Research Design; Research Personnel; Research Project Grants; Residual state; Respondent; Sampling; Science; Scientist; Series; Statistical Methods; Statistical Models; Structure; Surveys; Taxon; Time; Training; Training Support; United States National Institutes of Health; Work; comparative; design; experience; interest; statistics; success; Address; Aging; Animal Model; Basic Science; Biological Process; Biological Sciences; Biology; Biology of Aging; Body Composition; Clinic; Communities; Comparative Biology; Comparative Study; Data; Dependence; Dependency; Development; Event; Face; Frequencies; Hand; Immune; Institute of Medicine (U.S.); Investigation; Investments; Knowledge; Leadership; Left; Longevity; Longitudinal Studies; Mathematics; Measurement; Methods; Modeling; National Research Council; Organism; Outcome; Phylogenetic Analysis; Procedures; Publications; Recording of previous events; Reporting; Reproducibility; Research; Research Design; Research Personnel; Research Project Grants; Residual state; Respondent; Sampling; Science; Scientist; Series; Statistical Methods; Statistical Models; Structure; Surveys; Taxon; Time; Training; Training Support; United States National Institutes of Health; Work; comparative; design; experience; interest; statistics; success

The Comparative Data Analytics Core (CDAC) will provide not only high-level customized statistical support for basic science investigators studying aging and energetics in diverse model organisms at UAB, but also a venue for development of de novo methods specially for such research, a nidus for training others at and beyond UAB in such research, and a platform for the dissemination of such methods to the aging research community at large. The core leadership comprises statistical scientists with a 20-year history of studying the interface of aging, energetics and body composition. They bring not only their statistical expertise, but their experience with and zeal for the science of comparative studies at the interface of aging and energetics. The need for specialized statistical expertise, training, and support in aging research is clear. Statistical analyses of aging research data provide many challenges. Aging research involves longitudinal analyses and modeling the dependency of multiple observations taken over time, and accommodating the missing data which commonly occurs with longitudinal studies. With time-to-event (e.g., survival) outcomes, left, right, and interval censoring add further complexities. Statistical approaches in comparative biology face challenges such as phylogenetic dependence among model residuals, complicating inference. Non-statistician researchers benefit from the support and involvement of statistical scientists who are deeply involved in the subject matter, who can tailor methods to the situation at hand, who work with the biologists from the beginning as an engaged part of the research team, who can discuss the methods with the biologists and explain the statistical procedures and who can develop new statistical methods for specific needs. To that end, the UAB CDAC offers the following specific aims: 1. To provide statistical support for UAB investigators studying the comparative energetics of aging, including traditional, specialized, and bespoke methods. 2. To provide statistical support for non-UAB investigators studying the comparative energetics of aging, including traditional, specialized, and bespoke methods. 3. To conduct high-level statistical investigations of secondary data to answer questions about the comparative energetics of aging. 4. To develop and evaluate statistical methods needed in the field of the comparative energetics of aging. 5. To provide an organized series of educational offerings on statistical methods for the comparative energetics of aging which permit dissemination of expertise and knowledge to the broader scientific community. An investment in this core will achieve dividends by catalyzing more informative and rigorous research on aging within the UAB NSC and for the community of aging researchers at large.

比较数据分析核心（CDAC）不仅将提供高级定制统计支持 用于研究UAB不同模型生物的衰老和能量学的基础科学研究者，但也是 专门用于此类研究的新方法的开发场所，用于培训其他人的Nidus和 在此类研究中超越UAB，以及向老化研究传播此类方法的平台 整个社区。核心领导包括具有20年历史的统计科学家 衰老，能量和身体组成的界面。他们不仅带来了统计专业知识，还带来了 在衰老和能量学界面上对比较研究科学的经验和热情。 对于衰老研究的专业统计专业知识，培训和支持的需求很明显。统计 老化研究数据的分析提供了许多挑战。衰老研究涉及纵向分析和 建模随着时间的推移进行的多个观察值的依赖，并适应丢失的数据 通常发生在纵向研究中。随着事件的时间（例如生存）结果，左，右， 间隔检查增加了进一步的复杂性。比较生物学中的统计方法面临挑战 作为模型残差之间的系统发育依赖性，使推理变得复杂。 非统计的研究人员受益于深深地的统计科学家的支持和参与 参与主题，谁可以针对手头的情况量身定制方法，谁与生物学家合作 从一开始就作为研究团队的参与部分，他们可以与生物学家讨论这些方法 并解释统计程序，以及谁可以针对特定需求开发新的统计方法。 为此，UAB CDAC提供了以下特定目标： 1。为UAB研究人员提供统计支持，研究衰老的比较能量学，包括 传统，专业和定制方法。 2。为了为研究衰老的比较能量学提供统计支持， 包括传统，专业和定制方法。 3。进行二级数据的高级统计调查，以回答有关 衰老的比较能量学。 4。在老化的比较能量学领域开发和评估所需的统计方法。 5。为比较提供有关统计方法的有组织的教育产品 衰老的能量学，允许将专业知识和知识传播给更广泛的科学 社区。 通过催化有关更多信息和严格的研究，对此核心的投资将获得股息 UAB NSC和整个老龄化研究人员社区的老化。