Core C

核心C

• 批准号: 10553035
• 负责人: Yuval Kluger
• 金额: $ 45.75万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-02 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10553035
• 关键词: Algorithms; Atlases; Basic Science; Bioinformatics; Biological; Biological Markers; Catalogs; Cell Aging; Cells; Cellular Indexing of Transcriptomes and Epitopes by Sequencing; Clinical Research; Communities; Computer Analysis; Core Facility; Data; Data Analyses; Data Coordinating Center; Data Set; Data Storage and Retrieval; Database Management Systems; Databases; Deposition; Development; Environment; Fatty acid glycerol esters; Generations; Genomics; Geroscience; Goals; Histology; Image; Immune; Inflammation; Informatics; Lead; Ligands; Link; Lymphoid Tissue; Maps; Measures; Metadata; Methodology; Methods; Mission; Modality; Molecular; Mus; Online Systems; Pathology; Pathway interactions; Peripheral Blood Mononuclear Cell; Process; Proteomics; Protocols documentation; Sampling; Spleen; Statistical Data Interpretation; Stromal Cells; System; Thymus Gland; Tissue Sample; Tissue Stains; Tissues; Translational Research; United States National Institutes of Health; Validation; Visualization software; Work; base; biomarker identification; biomarker signature; biomarker validation; cell type; computer infrastructure; computerized data processing; data analysis pipeline; data modeling; data resource; data sharing; data standards; data visualization; database design; feature selection; graphical user interface; high dimensionality; informatics infrastructure; interoperability; member; mouse model; multidimensional data; multimodal data; multiple omics; multiscale data; next generation; quality assurance; receptor; senescence; software development; tool; transcriptome sequencing; transcriptomics; web portal

SUMMARY – Core C: Data Analysis Core (BAC) The Data Analysis Core (DAC) will build on available computational infrastructure to fulfill all the needs for advanced data analysis and informatics of Yale murine-TMC. It will also support data storage & sharing, metadata management & referencing, integration & query via a web portal, and rigorous statistical analyses to accomplish the Center's missions. The DAC is led by Dr. Kluger, who provides prominent expertise in bioinformatics and computational analysis of multi-dimensional data. He as an extensive track record of methodology development and led major efforts in analyzing genomics, proteomics, and high-plex imaging data in NIH consortia. Co-lead Gershkovich, Director of Yale Pathology Informatics infrastructure, software development, and system management, will provide important expertise in building frameworks and portals for integrating biospecimen meta data with biological analysis data from multiple modalities including omics and images. Core C will be responsible for 1) data Processing – to set up a set of multiscale and multimodal data processing pipelines and quality assurance protocols. 2) Data Analysis – to establish an integrated single-cell & spatial data analysis workflow to detect different types of senescence biomarker signatures. 3) Data Analysis – to establish an integrated single-cell & spatial data analysis workflow to detect different types of senescence biomarker signatures.4) Consortium Coordination – to work with the CODCC and other TMCs to develop data models, databases, design and visualization tools, and create new interoperability mechanisms and platforms. These are highly valuable next-generation biomedical data resources for NIH TMC consortia and the broader community of basic research and Geroscience .

摘要-核心C：数据分析核心(BAC) 数据分析核心(DAC)将建立在可用的计算基础设施之上，以满足以下所有需求 耶鲁大学高级数据分析和信息学-TMC。它还将支持数据存储和共享， 通过门户网站管理和引用、集成和查询元数据，并进行严格的统计分析，以 完成中心的使命。DAC由Kluger博士领导，他在以下方面提供卓越的专业知识 生物信息学和多维数据的计算分析。他作为一个广泛的跟踪记录 开发方法学，并在分析基因组学、蛋白质组学和高复合体成像数据方面领导主要工作 在NIH财团。耶鲁大学病理信息学基础设施、软件主管Gershkovich联席领导 开发和系统管理将在构建框架和门户方面提供重要的专业知识 将生物谱元数据与来自多个模式的生物分析数据集成，包括组学和 图像。核心C将负责1)数据处理-建立一组多尺度、多模式的数据 加工管道和质量保证协议。2)数据分析--建立一体化的单细胞& 空间数据分析工作流程，以检测不同类型的衰老生物标志物签名。3)数据分析- 建立集成的单细胞和空间数据分析工作流程，以检测不同类型的衰老 生物标志物签名。4)联盟协调-与CODCC和其他TMC合作开发数据 模型、数据库、设计和可视化工具，并创建新的互操作性机制和平台。 这些都是NIH TMC财团和更广泛的下一代生物医学数据资源 基础研究和老年科学社区。