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

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）不仅提供高级定制统计支持 为 UAB 的基础科学研究人员研究不同模型生物的衰老和能量学提供帮助，同时也为 专门为此类研究开发从头方法的场所，是培训其他人的场所 在此类研究中超越UAB，并为老龄化研究传播此类方法的平台 整个社区。核心领导层由具有 20 年研究经验的统计科学家组成 衰老、能量学和身体成分的界面。他们不仅带来了统计专业知识，还带来了 对衰老和能量学界面的比较研究科学有经验和热情。 老龄化研究显然需要专门的统计专业知识、培训和支持。统计 衰老研究数据的分析提出了许多挑战。老龄化研究涉及纵向分析和 对随时间推移进行的多次观察的依赖性进行建模，并容纳缺失的数据 这通常发生在纵向研究中。对于事件发生时间（例如生存）结果，左、右和 间隔审查进一步增加了复杂性。比较生物学的统计方法面临以下挑战 作为模型残差之间的系统发育依赖性，使推理变得复杂。 非统计学家研究人员受益于深入了解统计科学家的支持和参与 参与主题，可以根据当前情况定制方法，与生物学家合作 从一开始就作为研究团队的一部分，可以与生物学家讨论方法 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 提出了以下具体目标： 1. 为 UAB 研究人员研究衰老的比较能量学提供统计支持，包括 传统的、专业的、定制的方法。 2. 为非 UAB 研究人员研究衰老的比较能量学提供统计支持， 包括传统的、专业的和定制的方法。 3. 对二手数据进行高水平统计调查，回答有关问题 衰老的比较能量学。 4. 开发和评估衰老比较能量学领域所需的统计方法。 5. 提供一系列有组织的关于统计方法的教育课程，以便进行比较 衰老能量学允许将专业知识和知识传播到更广泛的科学领域 社区。 对这一核心的投​​资将通过促进更多信息丰富和严格的研究来实现红利 UAB NSC 内的老龄化问题以及整个老龄化研究人员群体的老龄化问题。