Biostatistics and Bioinformatics Core

项目总结（见说明）：衰老可能是最复杂的表型，很可能有多种遗传和环境因素影响长寿。与长寿相关的数据很难分析，需要最先进的统计方法。生物统计学和生物信息学核心（核心C）的主要活动是帮助研究概念化和规划，并支持统计分析。在目前的资助期内，生物统计学和生物信息学核心为研究人员提供了咨询和分析支持。研究前提供咨询，以确保适当的设计，研究后的统计服务包括数据分析和结果解释咨询。核心人员协助研究人员撰写他们的研究结果，形成了几份合作手稿。生物统计学和生物信息学核心还为项目研究人员开发了基于网络的数据库，并利用该数据库促进研究人员之间的互动和研究思想的交流，以培育新的方向。生物统计学和生物信息学核心的具体目标是：(1)协调和管理整个计划中的统计活动，以确保研究人员随时可以获得统计咨询和支持；(2)为新研究的设计提供统计专业知识，包括终点定义、样本量和功率计算、随机化程序、数据收集、报告生成计划、中期审查和所有子项目的最终统计分析；(3)提供数据库开发和管理方面的专业知识，开发数据挖掘工具，协调数据库，以便在项目/核心之间以及与科学界共享数据；(4)开发新的实验设计和统计分析的统计方法。所开发的方法将在最大程度上不仅根据参与整个计划的研究人员的需要，而且根据科学界的需要进行调整。

PROJECT SUMMARY (See instructions): Aging is perhaps the most complex phenotype, and it is likely that there are multiple genetic and environmental contributors to longevity. Longevity-related data are challenging to analyze and require state of- the-art statistical methods. The primary activities of the Biostatistics and Bioinformatics Core (Core C) are to help with research conceptualization and planning, and support of statistical analyses. During the current funding period, the Biostatistics and Bioinformatics Core has provided advice and analytic support to investigators. Before-study consultation was provided to ensure appropriate design, and after-study statistical services included data analysis and consultation on interpretation of results. The core aided investigators in writing up their results, resulting in several collaborative manuscripts. The Biostatistics and Bioinformatics Core also developed the web-based database for the program investigators and utilized the database to facilitate interactions and interchange of research ideas among the investigators in order to foster new directions. The specific aims of the Biostatistics and Bioinformatics Core are to: (1) coordinate and manage statistical activities in the overall program to ensure that investigators have ready access to statistical consultation and support; (2) provide statistical expertise for the design of new studies, including endpoint definition, sample size and power calculations, randomization procedures, data collection, plans for report generation, interim reviews, and final statistical analysis for all subprojects; (3) provide expertise in database development and management, develop data mining tools, and coordinate databases for data sharing among the projects/cores and with the scientific community; and (4) develop statistical approaches for novel experimental designs and statistical analyses. Methods to be developed will be, to the greatest extent possible, tailored to the needs of not only investigators involved in the overall program, but also the scientific community.