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: 10683113
• 负责人: Bruce J Aronow
• 金额: $ 145.84万
• 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/10683113
• 关键词: 3-Dimensional; Acceleration; 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 Coordinating Center; Data Provenance; Data Science; Data Set; Data Store; Deposition; Development; Disease; Engineering; Ensure; Environment; FAIR principles; Fostering; Funding; Generations; Genomics; Goals; Human; Human BioMolecular Atlas Program; Image; Image Analysis; Individual; Ingestion; 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; Site; Specialist; Specific qualifier value; Standardization; Structural Models; Structure; Systems Biology; Technology; Time; Tissue imaging; United States National Institutes of Health; Validation; Variant; Visualization; Work; application programming interface; body system; cell type; cloud storage; computerized data processing; data access; data dissemination; data format; data harmonization; data hub; data ingestion; data integration; data portal; data resource; data sharing; data standards; data visualization; design; experience; high resolution imaging; human tissue; improved; insight; interactive tool; interoperability; large scale data; literacy; lung development; lung maturation; metadata standards; multidimensional data; multidisciplinary; multiple omics; new technology; online resource; outreach; programs; repository; single-cell RNA sequencing; skills training; social; success; tool; two-dimensional; 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 LUNGMAP 2计划将创建新生儿、儿童和早期成人人类的详细分子图谱 肺，使人们能够更好地理解功能和解剖定义的细胞类型。数据 协调中心将作为龙图2号S集体知识和活动的纽带。这个 DCC负责数据整理、重新分析和集成；二次注记跟踪；开发 促进收集、共享和数据传播的工具；运营数据、专业知识和 协作；协调研究中心(RCS)和人体组织核心的活动。这个 DCC还将促进调查人员使用开发的工具和最佳做法进行分析、数据 来源和元数据注释，并参与更大的研究社区。为了主办DCC，我们有 组建了一个拥有数据网络领导力的多学科团队，以及单细胞基因组学领域的领导者， 图像分析、功能推理和数据再利用。DCC利用CCHMC的独特专业知识， UCSC和布罗德研究所互操作面向肺的单细胞和高分辨率成像数据 与其他地图集项目合作。我们还将世界知名的肺部研究人员纳入我们的领导团队，以 确保我们向研究界提供的数据和知识具有最大的科学影响。 总体而言，我们建议通过协调各基金之间的努力来加快LUNGMAP的科学议程 中心、美国国立卫生研究院和肺部研究社区；交叉验证、注释、存放和链接 包含分子组学、成像和相关结构的联合数据集和元数据 模型；并允许在LUNGMAP和研究社区内共享数据、结果和模型。 来自RCS的数据集和结果预计将对肺部产生重要的新见解 成熟、供体内变异和疾病发病机制。以确保由 RCS是可查找的、可访问的、可互操作的和可重复使用的(公平)，DCC将与RCS密切合作以 建立和共享最佳实践，协调元数据注释，确保研究得到充分支持， 协助存放统一的高完整性数据，以确保储存库的安全，并提供数据访问 和标准化的分析工作流程。通过结构化本体论的持续发展和 将使用新出现的最佳做法对元数据框架、RC派生的数据集进行注释和协调。 DCC将在新技术出现时支持数据和分析的摄取和验证。 我们将支持生成兼容的集中式、支持云的数据处理工作流 与HubMAP、Brain和HCA等外部倡议合作。我们希望在一个 启用Web的LongMAP Commons将促进许多利益相关者之间的互动。这将使 LUNGMAP DCC将成为数据共享、数据集成、协作和假设生成的枢纽 研究肺部发育和疾病的研究人员。

项目成果

AB569, a nontoxic chemical tandem that kills major human pathogenic bacteria.

AB569 是一种无毒化学串联物，可杀死主要的人类致病细菌。

• DOI: 10.1073/pnas.1911927117
• 发表时间: 2020
• 期刊: Proceedings of the National Academy of Sciences of the United States of America
• 影响因子: 11.1
• 作者: McDaniel,CameronT;Panmanee,Warunya;Winsor,GeoffreyL;Gill,Erin;Bertelli,Claire;Schurr,MichaelJ;Dongare,Prateek;Paul,AndrewT;Ko,Seung-HyunB;Lau,GeeW;Dasgupta,Nupur;Bogue,AmyL;Miller,WilliamE;Mortensen,JoelE;Haslam,David
• 通讯作者: Haslam,David