Core E - Comparative Data Analytics Core

核心 E - 比较数据分析核心

• 批准号: 10633299
• 负责人: DAVID B ALLISON
• 金额: $ 14.16万
• 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 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10633299
• 关键词: Academy; Address; Aging; Agreement; Anatomy; Basic Science; Bioenergetics; Biological Sciences; Biology; Biology of Aging; Body Composition; Clinic; Collaborations; Communities; Comparative Biology; Comparative Study; Competence; Computational Science; Computers; Data; Data Analytics; Dependence; Development; Discipline; Engineering; Event; Face; Frequencies; Genomics; Hand; Health; Investigation; Investments; Leadership; Learning; Left; Longevity; Longitudinal Studies; Mathematics; Measurement; Medicine; 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; Statistical Data Interpretation; Statistical Methods; Statistical Models; Structure; Surveys; Time; Training; United States National Institutes of Health; Work; comparative; computer science; design; experience; health science research; higher level mathematics; longitudinal analysis; mathematical sciences; model organism; statistics; success

Project Summary – Comparative Data Analytics Core The Comparative Data Analytics Core (Analytics Core) 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 and a platform for the dissemination of such methods to the aging research community at large. The core leadership comprises statistical scientists with decades of combined 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 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 that commonly occurs with longitudinal studies. Left, right, and interval censoring add further complexities with time-to-event (e.g., survival) outcomes. Statistical approaches in comparative biology face challenges such as phylogenetic dependence among model residuals that complicate 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 Analytics Core offers the following specific aims: Specific Aims 1/2: To provide statistical support for 1) UAB investigators and 2) non-UAB investigators studying the comparative energetics of aging, including traditional, specialized, and bespoke methods. Specific Aim 3: To conduct high-level statistical investigations of secondary data to answer questions about the comparative energetics of aging. Specific Aim 4: To develop and evaluate statistical methods needed in the field of the comparative energetics of aging. Specific Aim 5: To provide reproducibility, verification, and transparency support for aging researchers. 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. 1 of 1

项目总结-比较数据分析核心