The LungMAP Data Coordination Center for Next Gen Systems Biology of Respiration

下一代呼吸生物学系统 LungMAP 数据协调中心

• 批准号: 9815844
• 负责人: Bruce J Aronow
• 金额: $ 120.63万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-23 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9815844
• 关键词: 3-Dimensional; Accountability; Adopted; Adult; Anatomy; Atlases; Awareness; BRAIN initiative; Benchmarking; Biological Assay; Cell Communication; Cells; Cellular Structures; Childhood; Clinical Data; Collaborations; Collection; Communication; Communities; Complex; Data; Data Analyses; Data Coordinating Center; Data Provenance; Data Science; Data Set; Deposition; Development; Dimensions; Disease; Engineering; Ensure; Environment; Fostering; Funding; Gap Junctions; Generations; Genomics; Goals; Human; Image; Image Analysis; Individual; Ingestion; Institutes; Knowledge; Laboratories; Leadership; Link; Lung; Lung diseases; Maps; Metadata; Methods; Modeling; Molecular; Molecular Profiling; Monitor; Morphology; Neonatal; Ontology; Operations Research; Organ; Pathogenesis; Patient Representative; Phase; Positioning Attribute; Process; Protocols documentation; Reproducibility of Results; Research; Research Personnel; Resolution; Resource Sharing; Respiration; Running; Science; Secure; Services; Specialist; Specific qualifier value; Standardization; Structural Models; Structure; Systems Biology; Technology; Time; Tissue imaging; United States National Institutes of Health; Validation; Variant; Work; application programming interface; base; body system; cell type; cloud storage; computerized data processing; data access; data format; data hub; data integration; data portal; data resource; data sharing; data visualization; experience; high resolution imaging; human tissue; improved; insight; interactive tool; interoperability; literacy; lung development; lung maturation; molecular imaging; multidimensional data; multidisciplinary; multiple omics; new technology; online resource; outreach; programs; repository; single-cell RNA sequencing; skills training; social; success; tool; web site; web-enabled

PROJECT SUMMARY The LungMAP 2 initiative will create detailed molecular maps of the neonatal, pediatric and early adult human lung to enable improved understanding of functionally and anatomically defined cell types. The Data Coordination Center (DCC) will serve as the nexus of LungMAP 2's collective knowledge and activities. The DCC is responsible for data collation, re-analysis, and integration; secondary annotation tracking; developing tools to facilitate collection, sharing and data dissemination; operating a web resource for data, expertise, and collaboration; and coordinating activities across the Research Centers (RCs) and Human Tissue Core. The DCC will also facilitate literacy for investigator use of developed tools and best practices for analysis, data provenance and metadata annotation, and engage the larger research community. To host the DCC, we have assembled a multidisciplinary team with data network leadership, along with leaders in single-cell genomics, image analysis, functional inference, and data re-utilization. The DCC leverages unique expertise at CCHMC, UCSC, and the Broad Institute to interoperate pulmonary-oriented single-cell and high-resolution imaging data with other atlas programs. We also include world-renowned pulmonary researchers into our leadership team to ensure the data and knowledge we provide to the research community has the greatest scientific impact. Collectively, we propose to accelerate the LungMAP scientific agenda by coordinating efforts across funded Centers, the NIH, and the pulmonary research community; cross-validate, annotate, deposit and link Consortium datasets and metadata that encompass molecular -omics, imaging, and associated structural models; and enable sharing of data, results, and models within LungMAP and the research community. The datasets and results derived from the RCs are expected to yield significant new insights into lung maturation, intra-donor variation and disease pathogenesis. To ensure the underlying data produced by the RCs is findable, accessible, interoperable and re-usable (FAIR), the DCC will work closely with the RCs to establish and share best practices, coordinate metadata annotation, ensure studies are sufficiently powered, assist with the deposition of harmonized data of high integrity to secure repositories, and provide data access and standardized analysis workflows. Through the continued development of structured ontologies and metadata frameworks, RC-derived datasets will be annotated and harmonized using emerging best practices. The DCC will support the ingestion and validation of data and analysis from new technologies as they emerge. We will support the generation of centralized, cloud-enabled data processing workflows that are compatible with external initiatives such as HubMAP, BRAIN, and the HCA. We expect that providing these functions in a web-enabled LungMAP Commons will promote interaction across many stakeholders. This will position the LungMAP DCC to become a hub for data sharing, data integration, collaboration and hypothesis generation for investigators studying lung development and disease.

项目总结