Crook Sharon, Gleeson Padraig, Howell Fred, Svitak Joseph, Silver R Angus
Department of Mathematics and Statistics, School of Life Sciences, and Center for Adaptive Neural Systems, Arizona State University, Tempe, AZ, USA.
Neuroinformatics. 2007 Summer;5(2):96-104. doi: 10.1007/s12021-007-0003-6.
Quantitative neuroanatomical data are important for the study of many areas of neuroscience, and the complexity of problems associated with neuronal structure requires that research from multiple groups across many disciplines be combined. However, existing neuron-tracing systems, simulation environments, and tools for the visualization and analysis of neuronal morphology data use a variety of data formats, making it difficult to exchange data in a readily usable way. The NeuroML project was initiated to address these issues, and here we describe an extensible markup language standard, MorphML, which defines a common data format for neuronal morphology data and associated metadata to facilitate data and model exchange, database creation, model publication, and data archiving. We describe the elements of the standard in detail and outline the mappings between this format and those used by a number of popular applications for reconstruction, simulation, and visualization of neuronal morphology.
定量神经解剖学数据对于许多神经科学领域的研究都很重要，并且与神经元结构相关的问题的复杂性要求整合来自多个学科的多个研究小组的研究成果。然而，现有的神经元追踪系统、模拟环境以及用于神经元形态数据可视化和分析的工具使用了多种数据格式，这使得以易于使用的方式交换数据变得困难。NeuroML项目旨在解决这些问题，在此我们描述一种可扩展标记语言标准——MorphML，它定义了一种用于神经元形态数据及相关元数据的通用数据格式，以促进数据和模型交换、数据库创建、模型发布以及数据存档。我们详细描述了该标准的元素，并概述了这种格式与一些用于神经元形态重建、模拟和可视化的流行应用所使用格式之间的映射关系。
