Data Science Core
Data Science Core
批准号:
10294802
负责人:
Guoqiang Yu
金额:
$29.14万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-08-15 至 2026-07-31
关键词:
3-DimensionalAnatomyArchitectureAreaAstrocytesAtlasesAutomobile DrivingBehaviorBrainChIP-seqCommunitiesConsumptionCoupledDataData AnalysesData FilesData Science CoreData SetElectron MicroscopyEnsureGene ExpressionGenesGenetic TranscriptionGoalsImageImaging DeviceIndividualInfrastructureInternetLightMapsMeasurementMetadataMethodsMicroscopyModelingNeuronsOnline SystemsPatternPositioning AttributeProteomicsProtocols documentationResearch PersonnelResearch Project GrantsResolutionServicesSpecific qualifier valueStructureSystemTechniquesVisualizationVisualization softwareanimal datacomputerized toolsdata analysis pipelinedata disseminationdata formatdata repositorydata sharing networksdata visualizationdesigndigitaldigital object identifierlight microscopymembermultiple data typesneural circuitopen sourceoperationtooltranscription factortranscriptome sequencinguser-friendlyweb based interfaceweb portalweb-based tool
中文摘要
项目概要:数据科学核心
数据科学资源核心的主要目的是收集,管理和分发
实验数据,以可视化分析结果,如结构和活性,并
为用户提供一个界面,以便在成像数据和组学上使用我们设计的方法
数据这一数字基础设施将以面向服务的多层形式实施
架构其他研究项目的产品将通过协议收集,
一个数字化的表现形式。然后,这些将通过空间配准统一在一个
通用坐标系确保数据具有适当的标志,
对关键图像的空间范围的测量是这一奋进的核心操作。与
内容适合统一的数据,随后将确定哪个数字
格式表示最适合每种数据类型,其目标是使它们易于
以在线界面呈现,供更广泛的科学界使用。数据文件
将以适当的格式在公共互联网上提供。从这里,一个用户-
将在一个平台上设计和实施一个友好的基于网络的界面,
astrocytic数据可视化,它本身重用了一流的开源可视化软件
for the web网络.该界面将确保用户可以轻松地在各个数据之间导航
还可以可视化跨域数据集之间的关系,
研究项目。该界面将使用户能够探索星形胶质细胞的成像数据
在大脑的不同位置收集,以及在大脑中的组学表达模式,
相应的区域。该界面还将提供星形胶质细胞网络的可视化。到
鼓励广泛共享所产生的数据资源,将创建高质量的元数据
包含在数据中来传达它的出处。数据产品将能够拥有其
拥有自己的数字对象标识符(DOI),与ORCID ID兼容,并嵌入
必要时将RRID输入系统。核心数据产品将进一步通过关键
联邦支持的数据共享资源,并将最佳做法应用于数据格式,
使用的传播技术。数据分析方法也将提供给用户
作为基于网络的计算服务,供用户分析他们自己的数据。
英文摘要
Project Summary: Data Science Core
The main purposes of the Data Science Resource Core are to collect, manage and distribute
experimental data, to visualize the analyzed results such as structure and activity, and to
provide an interface for users to use our designed methods on both imaging data and omics
data. This digital infrastructure will be implemented in the form of a multi-tier services-oriented
architecture. The products of the other Research Projects will be collected via protocols that are
amenable to a digital representation. These will then be unified via spatial registration in a
common coordinate system. Ensuring that the data have appropriate landmarks and that
measurements of the spatial extent of key images is a core operation for this endeavor. With
data whose content is appropriate for unification, it will subsequently be determined which digital
format representation is most suitable for each data type, with the goal of making them easy to
present in an online interface for the consumption of the broader scientific community. Data files
with the appropriate format will be made available on the public internet. From here, a user-
friendly web-based interface will be designed and implemented on top of a platform for
astrocytic data visualization, that itself reuses best-in-class open-source visualization software
for the web. The interface will ensure that users can easily navigate between individual data
sets and also can visualize relationships between data sets across the domains from the other
Research Projects. The interface will enable the user to explore imaging data of astrocytes
collected at different positions of the brain, as well as the omics expression pattern at the
corresponding area. The interface will also provide the visualization of the astrocyte network. To
encourage broad sharing of the data resources produced, high quality metadata will be created
to include with the data that conveys its provenance. Data products will be enabled to have their
own digital object identifiers (DOIs), incorporate compatibility with ORCID ids, and embed
RRIDs into the system as necessary. Core data products will further be shared through key
federally supported data sharing resources and by applying best practices to data format and
dissemination techniques used. The data analysis method will also be made available for users
as web-based computational services for users to analyze their own data.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
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批准号:10461224
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High-density optical tomography of cerebral blood flow and metabolism in small animals
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批准号:10323090
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资助金额:$34.12万
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财政年份:2021
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依托单位:
High-density optical tomography of cerebral blood flow and metabolism in small animals
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批准号:10461939
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批准号:10204279
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财政年份:2020
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负责人:Guoqiang Yu
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Perioperative Diffuse Optical Imaging of Tissue Blood Flow and Oxygenation for Optimization of Mastectomy Skin Flap Viability
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批准号:10559475
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Noninvasive Noncontact High-Density Optical Imaging of Neonatal Intraventricular Hemorrhage
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财政年份:2020
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依托单位:
Noninvasive Noncontact High-Density Optical Imaging of Neonatal Intraventricular Hemorrhage
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Decoding Astrocyte Signaling in Neural Circuitry with Novel Computational Modeling and Analytical Tools
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财政年份:2017
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依托单位:
Decoding Astrocyte Signaling in Neural Circuitry with Novel Computational Modeling and Analytical Tools
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Non-contact Diffuse Optical Assessment of Pressure Ulcer and Therapy
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Non-contact Diffuse Optical Assessment of Pressure Ulcer and Therapy
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财政年份:2012
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Diffuse Optical Monitoring of Head and Neck Tumor Therapy
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批准号:8657873
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财政年份:2010
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Diffuse Optical Monitoring of Head and Neck Tumor Therapy
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批准号:8449694
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财政年份:2010
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Diffuse Optical Monitoring of Head and Neck Tumor Therapy
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依托单位:
海外基金