Suppr超能文献

“表面管理系统”(SuMS)数据库:一个基于表面的数据库,用于辅助皮质表面重建、可视化和分析。

'The surface management system' (SuMS) database: a surface-based database to aid cortical surface reconstruction, visualization and analysis.

作者信息

Dickson J, Drury H, Van Essen D C

机构信息

Department of Anatomy and Neurobiology, Washington University School of Medicine, St Louis, MO 63110, USA.

出版信息

Philos Trans R Soc Lond B Biol Sci. 2001 Aug 29;356(1412):1277-92. doi: 10.1098/rstb.2001.0913.

Abstract

Surface reconstructions of the cerebral cortex are increasingly widely used in the analysis and visualization of cortical structure, function and connectivity. From a neuroinformatics perspective, dealing with surface-related data poses a number of challenges. These include the multiplicity of configurations in which surfaces are routinely viewed (e.g. inflated maps, spheres and flat maps), plus the diversity of experimental data that can be represented on any given surface. To address these challenges, we have developed a surface management system (SuMS) that allows automated storage and retrieval of complex surface-related datasets. SuMS provides a systematic framework for the classification, storage and retrieval of many types of surface-related data and associated volume data. Within this classification framework, it serves as a version-control system capable of handling large numbers of surface and volume datasets. With built-in database management system support, SuMS provides rapid search and retrieval capabilities across all the datasets, while also incorporating multiple security levels to regulate access. SuMS is implemented in Java and can be accessed via a Web interface (WebSuMS) or using downloaded client software. Thus, SuMS is well positioned to act as a multiplatform, multi-user 'surface request broker' for the neuroscience community.

摘要

大脑皮层的表面重建在皮层结构、功能和连接性的分析与可视化中应用越来越广泛。从神经信息学的角度来看,处理与表面相关的数据存在诸多挑战。这些挑战包括表面常规查看的多种配置(例如膨胀图、球体和平坦图),以及可以在任何给定表面上表示的实验数据的多样性。为应对这些挑战,我们开发了一种表面管理系统(SuMS),它能够自动存储和检索复杂的与表面相关的数据集。SuMS为多种类型的与表面相关的数据及相关体数据的分类、存储和检索提供了一个系统框架。在这个分类框架内,它充当一个能够处理大量表面和体数据集的版本控制系统。借助内置的数据库管理系统支持,SuMS提供了跨所有数据集的快速搜索和检索功能,同时还纳入了多个安全级别来规范访问。SuMS用Java实现,可以通过Web界面(WebSuMS)或使用下载的客户端软件进行访问。因此,SuMS完全有能力作为神经科学界的多平台、多用户“表面请求代理”。

相似文献

9
GODIVA2: interactive visualization of environmental data on the Web.GODIVA2:网络环境数据交互式可视化
Philos Trans A Math Phys Eng Sci. 2009 Mar 13;367(1890):1035-9. doi: 10.1098/rsta.2008.0180.
10
PaVESy: Pathway Visualization and Editing System.PaVESy:通路可视化与编辑系统。
Bioinformatics. 2004 Nov 1;20(16):2841-4. doi: 10.1093/bioinformatics/bth278. Epub 2004 Apr 22.

引用本文的文献

4
The Brain Analysis Library of Spatial maps and Atlases (BALSA) database.大脑空间图谱与图谱集分析库(BALSA)数据库
Neuroimage. 2017 Jan;144(Pt B):270-274. doi: 10.1016/j.neuroimage.2016.04.002. Epub 2016 Apr 10.
6
Cartography and connectomes.制图学与连接组学。
Neuron. 2013 Oct 30;80(3):775-90. doi: 10.1016/j.neuron.2013.10.027.
8
CoCoMac 2.0 and the future of tract-tracing databases.CoCoMac 2.0 和轨迹追踪数据库的未来。
Front Neuroinform. 2012 Dec 27;6:30. doi: 10.3389/fninf.2012.00030. eCollection 2012.
9
Multiple imputation of missing fMRI data in whole brain analysis.全脑分析中缺失 fMRI 数据的多重插补。
Neuroimage. 2012 Apr 15;60(3):1843-55. doi: 10.1016/j.neuroimage.2012.01.123. Epub 2012 Feb 10.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验