Data Management Core: Systems Biology to Identify Biomarkers of Neonatal Vaccine Immunogenicity

数据管理核心：识别新生儿疫苗免疫原性生物标志物的系统生物学

• 批准号: 10063820
• 负责人: AL OZONOFF
• 金额: $ 24.55万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-12-27 至 2023-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10063820
• 关键词: Age; Architecture; Archives; Atlases; Biological; Biological Markers; Biometry; Clinical; Clinical Data; Clinical Services; Collaborations; Communities; Computer software; Consultations; Data; Data Files; Data Sources; Data Storage and Retrieval; Database and Analysis Portal; Environment; Experimental Designs; Fostering; Gene Expression; Goals; Guidelines; Human; Human Resources; Immune; Immunization; Immunology; In Vitro; Infrastructure; Institution; Investigation; Lead; Life; Link; Metadata; Methods; Neonatal; Newborn Infant; Peptides; Personnel Staffing; Phenotype; Plasma; Process; Productivity; Proteins; Proteomics; Research; Research Personnel; Research Support; Secure; Security; Services; Signal Transduction; Site; System; Systems Analysis; Systems Biology; United States National Institutes of Health; Vaccination; Vaccines; Variant; Work; analytical tool; archive data; archived data; base; bioinformatics infrastructure; bioinformatics tool; cloud based; cloud storage; computerized tools; computing resources; data access; data acquisition; data infrastructure; data integration; data management; data sharing; data tools; demographics; design; digital; experimental study; heterogenous data; high risk; immunogenicity; infection risk; insight; operation; predictive signature; programs; public repository; quality assurance; relational database; repository; response; success; synergism; transcriptome sequencing; transcriptomics; web services

PROJECT SUMMARY The overarching goal of the proposed Human Immunology Project Consortium (HIPC) is to characterize vaccine-induced biological variations (transcriptomic/proteomic; summarized as ‘OMIC’) in the human newborn that correlate with downstream immunogenicity as predictors for Correlates of Protection (CoPs). 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 and facilitate collaborations between the HIPC Projects and Cores. The DMC will also facilitate data sharing, submission to public repositories, and HIPC engagement with the external research community. The broad goals of the DMC are reliable data capture and retention; ongoing quality assurance; and provision of access/computational resources for integrative analyses. We articulate these goals through three Specific Aims: Aim 1: Create a secure data management infrastructure for data acquisition and retention from HIPC Clinical Core Sites, Service Cores, and Projects. Aim 2: Establish HIPC-wide quality assurance processes and accepted standards for each of the heterogeneous data sources. Aim 3: Provide biostatistical and bioinformatics tools and expertise to lead integrative analyses across platforms. Our data management architecture will rely on new capabilities at our institution to access Amazon Web Services (AWS) for reliable cloud-based research support. We have worked closely with our Research Computing department to implement a system for HIPC collaborators that will combine security and reliability with ease of access and the most advanced computational tools and resources available. We believe our approach will offer many advantages over a more traditional server-based architecture, not the least of which is a more fruitful computing environment for integrative analyses and scientific discovery. Scientific endeavors of this scope/scale require robust data management plans, infrastructure, and operations. Practical data integration requires an environment within which these data can be linked across platforms. The DMC’s function will build on close integration of project/core leads into the DMC (eg, Drs. Steen, Tebbutt, Brinkman, Foster and Hancock) thereby synergistically leveraging their distinct strengths and augmenting the the productivity and impact of our proposed program. Completion of our Specific Aims will enable fresh insights into the biological basis underlying vaccine protective responses in early life, informing rational design of effective vaccines for the very young who are at highest risk from infections.

项目摘要 拟议的人类免疫学项目联盟（HIPC）的总体目标是表征 人类新生儿中疫苗诱导的生物学变异（转录组/蛋白质组学；总结为“ Omic”） 这与下游免疫原性相关，作为保护相关的预测因子（COPS）。数据 管理核心（DMC）将建立并维护基于云的发现环境，由数据组成 存储和计算工具，以执行集成系统分析并促进合作 HIPC项目和核心。 DMC还将促进数据共享，提交给公共存储库以及 HIPC与外部研究社区的互动。 DMC的广泛目标是可靠的数据 捕获和保留；持续的质量保证；并为访问/计算资源提供 综合分析。我们通过三个具体目标来表达这些目标： 目标1：创建一个安全的数据管理基础架构，以从HIPC临床中获取和保留数据 核心站点，服务核心和项目。 目标2：建立HIPC范围内的质量保证过程和公认的标准 异构数据源。 目标3：提供生物统计学和生物信息学工具和专业知识，以领导跨越综合分析 平台。 我们的数据管理体系结构将依靠我们机构的新功能来访问Amazon Web 服务（AWS），用于可靠的基于云的研究支持。我们与研究紧密合作 计算部门为HIPC合作者实施系统，以结合安全性和可靠性 易于访问和最先进的计算工具和资源。我们相信我们的 方法将提供比基于服务器基于服务器的架构的许多优势，其中最重要的是 一个更富有成果的计算环境，用于综合分析和科学发现。 这项范围/量表的科学努力需要强大的数据管理计划，基础架构和运营。 实用数据集成需要一个环境，可以使这些数据可以跨平台链接。这 DMC的函数将基于将项目/核心导线密切集成到DMC的基础上（例如 Brinkman，Foster和Hancock）从而协同利用其独特的优势并增强 我们提议的计划的生产力和影响。完成我们的特定目标将使新见解 成为生物基础疫苗的生物基础，以保护早期的反应，从而为理性设计提供 感染风险最高的年轻人的有效疫苗。