Meaningful data integration, visualization and distribution for Human Pain Associated Genes & Cells Datasets

人类疼痛相关基因的有意义的数据集成、可视化和分布

• 批准号: 10806601
• 负责人: Peter John Hunter
• 金额: $ 444.63万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-30 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10806601
• 关键词: 3-Dimensional; Acceleration; Anatomy; Architecture; Bioinformatics; Cell physiology; Cells; Chromosome Mapping; Collaborations; Communication; Communities; Data; Data Collection; Data Management Resources; Data Set; Development; Education and Outreach; Ensure; Environment; Fostering; Genes; Goals; Helping to End Addiction Long-term; Human; Image; Individual; Infrastructure; Intuition; Investigation; Knowledge; Knowledge Management; Label; Lead; Maps; Metadata; Molecular Profiling; Neurosciences; Output; Pain; Pathway interactions; Peripheral; Persons; Phenotype; Physiological; Physiology; Privatization; Protocols documentation; Publications; Publishing; Research; Research Personnel; Resource Sharing; Resources; Secure; Semantics; Signal Transduction; Standardization; System; Tissues; Translations; United States National Institutes of Health; Visualization; Visualization software; Vocabulary; Work; cell type; complex data; data curation; data ecosystem; data exploration; data integration; data management; data repository; data resource; data sharing; data standards; data submission; data visualization; improved; information organization; inter-institutional; knowledge graph; knowledge integration; meetings; novel; outreach; pain signal; programs; repository; scaffold; technology platform; tool; transmission process; web app

Project Summary: The PRECISION Human Pain project has a primary goal to develop a comprehensive datasets of molecular signature cell types, and cellular function phenotypes or signatures that underlie human pain signal transduction, transmission, and processing. To maximize the impact of the data generated through this effort, it is vital to standardize and integrate all data generated by the U19 centers and make these data available in a meaningful way to the larger scientific community. As the data coordination and integration center, we will support the PRECISION Heal initiative to generate a high impact resource for sharing, visualizing datasets, and making these datasets actionable for downstream analysis and scientific investigations. Over the last 7 years, our interdisciplinary team has developed platform technologies, standards, and visualization mechanisms to look at physiological data in context for several NIH programs (e.g. SPARC and REJOIN). Our combined domain expertise spans the requirements to facilitate complex data integration specifically for Neuroscience and physiology datasets. We will leverage our existing platform technologies and workflows to rapidly engage with the HEAL PRECISION U19 centers and lead the effort to develop the knowledge and data integration capabilities needed to support high impact research. We will expand our workflows to be tightly integrated with the existing HEAL Data Ecosystem, its repositories, and any workflow and data integration requirements by the individual U19 data cores. In this proposal our goals are: (1) To develop a data management and knowledge platform for HEAL Precision centers to standardize datasets across the HEAL Precision U19 data collection centers, provide the means to share data amongst the consortium in a meaningful way prior to data publication and integrate knowledge across all submitted data (2) To develop novel visualization and data exploration mechanisms to interact with these data in context as part of an integrated data ecosystem. (3) To increase the impact of the HEAL PRECISION program through operational support, outreach and educational efforts. This project leverages an established inter institutional collaboration between investigators across BioInformatics, Physiology and Knowledge Management with a track record of successfully supporting large NIH efforts with data resource management.

项目摘要： 精密人类疼痛项目的主要目标是开发分子的全面数据集 签名细胞类型以及源于人类疼痛信号的蜂窝功能表型或特征 转导，传输和处理。为了最大化通过这项工作产生的数据的影响， 对于标准化和整合U19中心生成的所有数据至关重要，并使这些数据可用于 对更大的科学界的有意义的方式。作为数据协调和集成中心，我们将 支持Precision Heal倡议，以生成用于共享，可视化数据集和的高影响资源 使这些数据集可用于下游分析和科学研究。在过去的7年中， 我们的跨学科团队已经开发了平台技术，标准和可视化机制 查看多个NIH程序的上下文中的生理数据（例如SPARC和重新加入）。我们的结合域 专业知识涵盖了专门针对神经科学的复杂数据集成的要求 生理数据集。我们将利用现有的平台技术和工作流程来迅速与 治愈精度U19中心并领导发展知识和数据集成的努力 支持高影响研究所需的能力。 我们将扩大工作流程，以与现有的Heal Data生态系统紧密整合在一起 存储库以及单个U19数据核心的任何工作流程和数据集成要求。在这个 建议我们的目标是：（1）为治疗精度开发数据管理和知识平台 在整个Heal Precision U19数据收集中心中标准化数据集的中心，提供手段 在数据发布之前以有意义的方式共享联盟中的数据并整合知识 在所有提交的数据（2）中，以开发新颖的可视化和数据探索机制以与 这些数据是集成数据生态系统的一部分。 （3）增加治愈的影响 精确计划通过运营支持，外展和教育工作。这个项目利用 在生物信息学，生理学和 知识管理具有成功支持数据资源的大型NIH努力的记录 管理。