The Human Body Atlas: High-Resolution, Functional Mapping of Voxel, Vector, and Meta Datasets

人体图谱：体素、矢量和元数据集的高分辨率功能映射

• 批准号: 10397321
• 负责人: KATY BORNER
• 金额: $ 150万
• 依托单位: TRUSTEES OF INDIANA UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-21 至 2022-06-20
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10397321
• 关键词: Anatomy; Artificial Intelligence; Atlases; Biology; Biometry; Cataloging; Cells; Collaborations; Communication; Data; Data Set; Ecosystem; Goals; Human; Human BioMolecular Atlas Program; Human body; Image; Individual; Infrastructure; Maps; Metadata; Methods; Modeling; Molecular; Organ; Resolution; Resources; Tissues; Visual; Visualization; Work; base; cell type; data exploration; data standards; design; human imaging; improved; interoperability; tool; vector

Project Summary/Abstract The ultimate goal of the HIVE MC-IU effort is to develop a common coordinate framework (CCF) for the healthy human body that supports the cataloguing, exploration, and download of differenttypes of tissue and individual cell data. The CCF will use different visual interfaces in order to exploit human and machine intelligence to improve data exploration and communication. The proposed effort combines decades of expertise in data and network visualization, scientific visualization, biology, and biomedical data standards. The goal is to develop a highly accurate and extensible multidimensional spatial basemap of the human body with associated data overlays. This basemap will be designed for online exploration as an atlas of tissue maps composed of diverse cell types, developed in close collaboration with the HIVE MC-NYGC team. To implement this functionality, we will develop methods to map and connect metadata, pixel/voxel data, and extracted vector data, allowing users to “navigate” across multiple levels (whole body, organ, tissue, cells). MC-IU will work in close collaboration with the HIVE Infrastructure and Engagement Component (IEC) and tools components (TCs) to connect and integrate further computational, analytical, visualization, and biometric resources driven by spatial context.

项目摘要/摘要 Hive MC-IU努力的最终目标是开发一个共同的坐标框架 （CCF）用于支持分类，探索和下载的健康人体 组织和单个细胞数据的不同类型。 CCF将在 为了利用人类和机器智能以改善数据探索和 沟通。拟议的努力结合了数十年的数据和网络专业知识 可视化，科学可视化，生物学和生物医学数据标准。目标是 发展人体的高度准确且可扩展的多维空间基础 与关联的数据叠加。该基础图将用于在线探索作为地图集 由潜水细胞类型组成的组织图，与蜂巢密切合作开发 MC-NYGC团队。为了实现此功能，我们将开发用于映射和连接的方法 元数据，像素/体素数据和提取的向量数据，使用户可以在 多个水平（全身，器官，组织，细胞）。 MC-IU将与 HIVE基础架构和参与组件（IEC）和工具组件（TCS） 连接并整合进一步的计算，分析，可视化和生物识别资源 由空间上下文驱动。

项目成果

Forecasting innovations in science, technology, and education

• DOI: 10.1073/pnas.1818750115
• 发表时间: 2018-12-11
• 期刊: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• 影响因子: 11.1
• 作者: Borner, Katy;Rouse, William B.;Stanley, H. Eugene
• 通讯作者: Stanley, H. Eugene

Visualizing learner engagement, performance, and trajectories to evaluate and optimize online course design

• DOI: 10.1371/journal.pone.0215964
• 发表时间: 2019-05-06
• 期刊: PLOS ONE
• 影响因子: 3.7
• 作者: Ginda, Michael;Richey, Michael C.;Borner, Katy
• 通讯作者: Borner, Katy

The impact of air transport availability on research collaboration: A case study of four universities

• DOI: 10.1371/journal.pone.0238360
• 发表时间: 2018-11
• 期刊: PLoS ONE
• 影响因子: 3.7
• 作者: Adam Ploszaj;Xiaoran Yan;K. Börner

Data visualization literacy: Definitions, conceptual frameworks, exercises, and assessments

• DOI: 10.1073/pnas.1807180116
• 发表时间: 2019-02-05
• 期刊: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• 影响因子: 11.1
• 作者: Boerner, Katy;Bueckle, Andreas;Ginda, Michael
• 通讯作者: Ginda, Michael