Multi-Scale Multi-Modality High Resolution Mapping of the Adult Human Lung

成人肺的多尺度多模态高分辨率测绘

• 批准号: 10530973
• 负责人: GLORIA S PRYHUBER
• 金额: $ 56.44万
• 依托单位: UNIVERSITY OF ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10530973
• 关键词: 3-Dimensional; Adult; Anatomy; Atlases; Cells; Collection; Consensus; Data; Data Analyses; Data Collection; Data Set; Data Storage and Retrieval; Ensure; Environment; Equipment; FAIR principles; Health Insurance Portability and Accountability Act; High Performance Computing; Human; Human BioMolecular Atlas Program; Human Resources; Image; Ingestion; Institution; Link; Location; Lung; Maps; Metadata; Modality; Molecular; Names; Ontology; Organ; Output; Positioning Attribute; Procedures; Process; Production; Protocols documentation; Reproducibility; Resolution; Resources; Role; Secure; Signal Transduction; Structure of parenchyma of lung; Systems Biology; Universities; Work; base; cluster computing; computerized data processing; data format; data ingestion; data integration; data quality; data sharing; experience; extracellular; indexing; interoperability; multi-scale atlas; multimodality; novel; open source tool; programs; spatial relationship; statistical and machine learning; tissue mapping; tool; virtual machine; 3-Dimensional; Adult; Anatomy; Atlases; Cells; Collection; Consensus; Data; Data Analyses; Data Collection; Data Set; Data Storage and Retrieval; Ensure; Environment; Equipment; FAIR principles; Health Insurance Portability and Accountability Act; High Performance Computing; Human; Human BioMolecular Atlas Program; Human Resources; Image; Ingestion; Institution; Link; Location; Lung; Maps; Metadata; Modality; Molecular; Names; Ontology; Organ; Output; Positioning Attribute; Procedures; Process; Production; Protocols documentation; Reproducibility; Resolution; Resources; Role; Secure; Signal Transduction; Structure of parenchyma of lung; Systems Biology; Universities; Work; base; cluster computing; computerized data processing; data format; data ingestion; data integration; data quality; data sharing; experience; extracellular; indexing; interoperability; multi-scale atlas; multimodality; novel; open source tool; programs; spatial relationship; statistical and machine learning; tissue mapping; tool; virtual machine

Project Summary/Abstract Data Analysis Core Synthesis of the Multimodality High Resolution 3-D Atlas of Human Lung The Data Analysis Core (DAC) is responsible for all aspects of data and metadata management, processing, analysis, mapping, and sharing for this Tissue Mapping Center (TMC) and of the Organ Specific Project focused on the adult healthy human lung (i.e., Lung Specific Project or LSP). We will take a long view of an Atlas, as a collection of 2D and 3D maps containing images, tabular data, facts about multiple locations at varying resolution and indexes of named objects keyed to coordinates of a locational grid analogous to latitude and longitude, to cartographically present the whole range of salient features of the human Lung. The DAC will support the TMC in these activities by providing a protected environment for data storage and computation, and by developing robust reproducible, reusable, and scalable computational workflows thus enabling the integration of data types into 3D maps for the purpose of creating an interactive and queryable biomolecular human atlas. The DAC is an essential part of the TMC in its objectives to produce and deliver to the HIVE extensive sets of high-resolution spatial mappings of molecular entities, using open formats, and within the context of the cellular and extracellular organization of the Lung. The DAC will accomplish its role through the following Specific Aims: 1) Ingest and process TMC datasets, 2) Analyze datasets in support of generating multiscale, multiparameter lung tissue maps, tabular data, and annotations, 3) Construct 2D and 3D lung tissue maps with integrated datasets and 4) Coordinate planning and atlas production with the HuBMAP Consortium.

项目摘要/摘要 数据分析核心 多模式高分辨率3-D地图集的合成人肺 数据分析核心（DAC）负责数据和元数据管理，处理， 该组织映射中心（TMC）的分析，映射和共享和特定器官项目的重点 在成人健康的人类肺（即肺特异性项目或LSP）上。我们将长时间了解一个地图集 收集包含图像，表格数据，关于多个位置的事实的2D和3D地图的收集 和命名对象的索引，该对象键入与纬度和经度类似的位置网格的坐标 在制图上呈现了人类肺的全部突出特征。 DAC将支持TMC 在这些活动中，通过为数据存储和计算提供受保护的环境，并通过开发 可重现，可重复使用和可扩展的计算工作流程，从而使数据类型的集成 进入3D地图，目的是创建一个交互式和可查询的生物分子人地图集。 DAC是 TMC的基本部分在其生产和交付到蜂巢广泛的高分辨率的目标中 分子实体的空间映射，使用开放格式，在细胞外的背景下 肺组织。 DAC将通过以下特定目的来完成其角色：1）摄入和 过程TMC数据集，2）分析数据集，以支持生成多尺度，多型肺组织 图，表格数据和注释，3）构造具有集成数据集的2D和3D肺组织图，4） 与Hubmap财团协调计划和地图集的生产。