Data Management & Analysis Core: IDEAL shapes vaccine response, susceptibility to respiratory infectious disease and asthma

项目概要：IDEAL数据管理核心（DMC） 拟议的生命早期免疫发育（IDEAL）项目的首要目标是采用系统 生物学来表征儿童免疫轨迹，以确定关键临床结果的内型， 如疫苗反应性、呼吸道感染和哮喘。为了支持这项工作，数据管理 核心（DMC）将建立和维护一个基于云的发现环境，包括数据存储和 计算工具，以执行临床数据、实验室样本管理和高性能的综合系统分析。 尺寸测定结果。DMC将促进IDEAL项目和核心项目之间的合作 包括数据共享、向公共知识库提交数据以及与外部研究团体合作。 DMC的主要目标是可靠的数据采集和保留、持续的质量保证（QA），以及 访问/计算资源进行综合分析。我们通过三个具体目标阐明这些目标， 包括建立用于数据采集、管理和分析的数字基础设施;严格的质量管理 控制（QC）和QA;以及生物统计学和生物信息学分析专业知识。 我们的数据管理架构是在改进机构能力的基础上设计的， 基于云的临床数据管理、实验分析QC/QA和分析支持。我们一直 与BCH研究计算部门密切合作，为IDEAL合作者实施一个系统， 联合收割机将安全性和可靠性与可访问性以及最先进的计算工具和资源相结合。我们 方法提供了许多优于传统的基于服务器的体系结构的优点，其中最重要的是 为综合分析和科学发现提供富有成效的协作计算环境。 任何这种范围和规模的科学奋进都需要强大的数据管理计划、基础设施和 运营实际上，如果没有一个环境来链接这些数据，就不可能实现实际的数据集成 平台DMC的综合功能对于充分利用IDEAL项目的独特优势是必要的 和核心的科学协同作用。我们希望我们的综合发现环境将增强科学 IDEAL研究的整体价值和生产力。DMC将使我们能够发现内型特异性 分子和途径，可作为预测临床结果的预后和/或可行生物标志物 和/或代表将IDEAL转向健康的干预措施的目标。

PROJECT SUMMARY: IDEAL Data Management Core (DMC) The overarching goal of the proposed immune development in early life (IDEAL) project is to employ systems biology to characterize childhood immune trajectories in order to define endotypes of key clinical outcomes such as vaccine responsiveness, respiratory infection and asthma. In support of this effort, the Data Management Core (DMC) will establish and maintain a cloud-based discovery environment, consisting of data storage and computational tools to perform integrative systems analyses of clinical data, lab sample management, and high dimensional assay results. The DMC will facilitate collaborations between the IDEAL Projects and Cores including data sharing, submission to public repositories, and engagement with the external research community. The broad goals of the DMC are reliable data capture and retention, ongoing quality assurance (QA), and access/computational resources for integrative analyses. We articulate these goals through three Specific Aims, including establishment of digital infrastructure for data capture, management, and analysis; rigorous quality control (QC) and QA; and biostatistical and bioinformatics expertise for analysis. Our data management architecture is designed on the basis of improved institutional capabilities for reliable cloud-based clinical data management, experimental assay QC/QA, and analytic support. We have worked closely with the BCH Research Computing Department to implement a system for IDEAL collaborators that will combine security and reliability with accessibility and state-of-the-art computational tools and resources. Our approach offers many advantages over more traditional server-based architecture, not the least of which is a fruitful collaborative computing environment for integrative analyses and scientific discovery. Any scientific endeavor of this scope and scale requires robust data management plans, infrastructure, and operations. Indeed, there can be no practical integration of data without an environment to link these data across platforms. The DMC’s integrative function is necessary to leverage the distinct strengths of the IDEAL projects and cores into scientific synergies. We expect our integrated discovery environment will augment the scientific value and productivity of the overall IDEAL study. The DMC will enable us to discover endotype-specific molecules and pathways, that may serve as prognostic and/or actionable biomarkers to predict clinical outcomes and/or that represent targets for interventions that redirect IDEAL towards health.