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

数据管理

• 批准号: 10589803
• 负责人: AL OZONOFF
• 金额: $ 21.78万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-10 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10589803
• 关键词: Architecture; Archives; Articulation; Asthma; Bioinformatics; Biological Assay; Biological Markers; Biometry; Child Health; Childhood; Clinical; Clinical Data; Collaborations; Communicable Diseases; Communities; Computer software; Data; Data Analyses; Data Analytics; Data Files; Data Set; Data Sources; Data Storage and Retrieval; Deposition; Development; Disease; Disparate; Environment; Experimental Designs; FAIR principles; Gene Expression; Goals; Health; Human Resources; Immune; Immune system; In Vitro; Infrastructure; Institution; Intervention; Knowledge; Life; Link; Metadata; Methods; National Institute of Allergy and Infectious Disease; Outcome; Pathway interactions; Personnel Staffing; Predisposition; Process; Productivity; Proteomics; Quality Control; Reproducibility; Reproduction; Research; Research Project Grants; Resources; Respiratory Tract Infections; Sampling; Secure; Security; Services; Shapes; Source; Statistical Data Interpretation; Systems Analysis; Systems Biology; United States National Institutes of Health; Vaccines; Work; archive data; biosignature; clinically relevant; cloud based; cloud storage; cohort; computerized tools; computing resources; data access; data acquisition; data archive; data infrastructure; data integration; data management; data sharing; data standards; demographics; design; digital; epigenomics; experimental analysis; heterogenous data; high dimensionality; improved; innovation; insight; metabolomics; microbiome; operation; predict clinical outcome; prognostic; public repository; quality assurance; relational database; repository; respiratory; response; sample collection; synergism; transcriptome sequencing; transcriptomics; user-friendly; vaccine response

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.

项目概述：IDEAL Data Management Core （DMC）