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MorphML: Level 1 of the NeuroML Standards for Neuronal Morphology Data and Model Specification

Authors
  • Crook, Sharon1
  • Gleeson, Padraig2
  • Howell, Fred3
  • Svitak, Joseph4
  • Silver, R. Angus2
  • 1 School of Life Sciences, and Center for Adaptive Neural Systems, Arizona State University, Department of Mathematics and Statistics, Tempe, AZ, USA , Tempe (United States)
  • 2 University College London, Department of Physiology, London, UK , London (United Kingdom)
  • 3 University of Edinburgh, Institute of Adaptive and Neural Computation, Edinburgh, UK , Edinburgh (United Kingdom)
  • 4 University of Texas Health Science Center at San Antonio, Research Imaging Center, San Antonio, TX, USA , San Antonio (United States)
Type
Published Article
Journal
Neuroinformatics
Publisher
Humana Press Inc
Publication Date
Apr 01, 2007
Volume
5
Issue
2
Pages
96–104
Identifiers
DOI: 10.1007/s12021-007-0003-6
Source
Springer Nature
Keywords
License
Yellow

Abstract

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.

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