A Community Resource for Single Cell Data in the Brain

项目摘要 对大脑中细胞类型特定数据的结构和作用的详细普查被认为是最重要的研究之一。 这是一个很有前途的途径，可以促进我们对人类大脑健康和疾病的理解。首要目标 该项目的目标是构建一个基础社区资源，用于存储以单单元为中心的数据内容， 个脑袋通过采用三层数据、工具和知识范式，我们将与数据生成一起发挥领导作用 合作伙伴，开发和部署基本数据模型，共同的社区标准， 科学结果，以提高我们对哺乳动物大脑中不同细胞类型的理解， 多维组织逻辑该项目提出了一个统一的解决方案，以开发其资源 首先是数据收集、量化和映射框架，用于管理数据和信息 跨不同的存储库。第一步是支持从数据中获取基本数据类型 通过开发数据模型和框架，将结构化数据导入BRAIN Cell Data， 中心（BCDC）采用一致的数据描述标准，描述并促进社区的最佳实践 使用多模态单细胞数据及其内容。为了实现这一目标，我们将与 神经科学信息框架（NIF），国际神经信息学协调机构（INCF）， 神经科学无国界（NWB）和其他标准促进组织利用和扩展 允许外部数据贡献者利用BCDC的现有标准。为了使这些数据具有连贯性、空间性 制图的共同坐标框架是必不可少的，该项目发展和扩展了艾伦研究所 鼠标通用坐标框架，可在2D和3D中实现关键单细胞模式的外部映射 在细胞、细胞核和/或群体水平上进行访问和可视化的解剖学背景。整个结果数据， 工具和知识将在一个统一的、集成的、可通过网络访问的细胞注册表中公开提供 以及支持数据检索、搜索、可视化和分析细胞特定数据和知识的Portal 合成. BCDC前端将提供数据特征摘要、工具和生成的知识，以及 原始数据和高分辨率图像，以及可编程的API/SDK，使社区能够构建 他们自己的分析应用程序和贡献工具。最后，我们将通过强大的BICCN扩大公众影响力 伙伴关系管理、沟通、标准委员会和分析工作组，并制定 用于最大限度地提高社区使用率、发布标准和教程以及协调教育的基础设施 和外联。

Project Summary A detailed census of the structure and role of cell type specific data in the brain is recognized as one of the most promising avenues for advancing our understanding of the human brain in health and disease. The primary goal of this project is to build a foundational community resource for housing single-cell centered data content in the brain. By adopting a three-tiered data, tools, and knowledge paradigm we will lead, together with data generation partners, in the development and deployment of fundamental data models, common community standards, and scientific results to improve our understanding of the diverse cell types in the mammalian brain and its three dimensional organizational logic. This project proposes a unified solution to the development of its resource beginning with a data collection, quantification, and mapping framework for managing data and information across diverse repositories. The first step is to support the acquisition of fundamental data types from data partners by developing the data models and framework for importing structured data into the BRAIN Cell Data Center (BCDC) in consistent data description standards that describe and facilitate best practices for community use of multi-modal single cell data and its content. Toward achieving this end, we will partner with the Neuroscience Information Framework (NIF), International Neuroinformatics Coordinating Facility (INCF), Neuroscience without Borders (NWB), and other standards promoting organizations to leverage and extend existing standards to allow external data contributors to utilize the BCDC. For these data to be coherent, spatial common coordinate frameworks for mapping are essential, and the project develops and extends Allen Institute Mouse Common Coordinate Framework to enable external mapping of key single cell modalities in a 2D and 3D anatomic context for access and visualization at cell, nuclei, and/or population level. The entire resulting data, tools, and knowledge will be made publicly available in a unified and integrated web-accessible Cell Registry and Portal supporting data retrieval, search, visualization, and analysis of cell specific data and knowledge synthesis. The BCDC front end will provide data feature summaries, tools, and resulting knowledge, and links to raw data and high-resolution images, together with a programmable API/SDK that allows the community to build their own analysis applications and contribute tools. Finally, we will amplify public impact through strong BICCN partnership management, communication, standards committees, and analysis working groups, and develop infrastructure for maximizing community usage, publishing standards and tutorials, and coordinating education and outreach.