Core E - Comparative Data Analytics Core

项目摘要-比较数据分析核心 比较数据分析核心（分析核心）不仅将提供高级定制统计数据， 支持基础科学研究人员在UAB研究不同模式生物的衰老和能量学，但 也是专门为此类研究开发从头方法的场所， 向整个老龄化研究界传播这种方法。核心领导层包括 拥有数十年研究衰老、能量学和身体界面历史的统计科学家 混合物.他们不仅带来了他们的统计专业知识，而且还带来了他们的经验和对科学的热情。 在老化和能量学的界面上进行比较研究。 老龄化研究显然需要专门的统计知识和支持。老龄化的统计分析 研究数据带来了许多挑战。老龄化研究包括纵向分析和建模， 随着时间的推移进行的多个观测的依赖性，并适应通常 进行纵向研究。左删失、右删失和区间删失增加了事件发生时间的复杂性 (e.g.,生存）的结果。比较生物学中的统计方法面临着诸如系统发育的挑战 模型残差之间的相关性使推断复杂化。 非统计学家的研究人员受益于统计科学家的支持和参与， 参与这一主题的人，谁可以根据手头的情况调整方法，谁与生物学家合作， 作为研究团队的一部分，他们可以与生物学家讨论方法， 解释统计程序，以及谁可以针对具体需要开发新的统计方法。 为此，Analytics Core提供了以下具体目标： 具体目标1/2：为1）UAB研究者和2）非UAB研究者提供统计支持 研究老化的比较能量学，包括传统的，专业的和定制的方法。 具体目标3：对二手数据进行高水平的统计调查，以回答问题 关于衰老的相对能量学 具体目标4：制定和评价比较研究领域所需的统计方法， 老化的能量学 具体目标5：为老龄化研究人员提供可重复性、验证性和透明度支持。 对这一核心的投资将通过催化对老龄化的更翔实和更严格的研究来实现红利 在UAB NSC和整个老龄化研究人员的社区。 1 of 1

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