ArticleNature communications2023
Online conversion of reconstructed neural morphologies into standardized SWC format.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- MASCAF: A Cable Model Fitting Pipeline for Topologically Complex Surface Meshes.bioRxiv : the preprint server for biology · 2026Article
- Automated Proofreading of Digitally Reconstructed Neural Morphology Enhances Accuracy, Scalability, and Standardization.bioRxiv : the preprint server for biology · 2026Article
- Alzheimer's Pathology Enhances Excitatory Synaptic Input and Integration in VTA Dopamine Neurons.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Article
- VENturing into machine learning for the morphological analysis of von Economo neurons.Scientific reports · 2025Article
- Dendritome mapping reveals the spatial organization of striatal neuron morphology.Nature neuroscience · 2025Article
- Mouse and human striatal projection neurons compared - somatodendritic arbor, spines and in silico analyses.PLoS computational biology · 2025Article
- PKC-dependent enhancement of glutamate input to VTA dopamine neurons in 3xTg-AD mice.bioRxiv : the preprint server for biology · 2025Article
- Article
- NeuroXiv: AI-powered open databasing and dynamic mining of brain-wide neuron morphometry.Nature methods · 2025Article
- A Multi-Scale Neuron Morphometry Dataset from Peta-voxel Mouse Whole-Brain Images.Scientific data · 2025Article
- Accelerating the continuous community sharing of digital neuromorphology data.FASEB bioAdvances · 2024Article
- Unsupervised classification of brain-wide axons reveals the presubiculum neuronal projection blueprint.Nature communications · 2024Article
- Online conversion of reconstructed neural morphologies into standardized SWC format.Nature communications · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Digital reconstructions provide an accurate and reliable way to store, share, model, quantify, and analyze neural morphology. Continuous advances in cellular labeling, tissue processing, microscopic imaging, and automated tracing catalyzed a proliferation of software applications to reconstruct neural morphology. These computer programs typically encode the data in custom file formats. The resulting format heterogeneity severely hampers the interoperability and reusability of these valuable data. Among these many alternatives, the SWC file format has emerged as a popular community choice, coalescing a rich ecosystem of related neuroinformatics resources for tracing, visualization, analysis, and simulation. This report presents a standardized specification of the SWC file format. In addition, we introduce xyz2swc, a free online service that converts all 26 reconstruction formats (and 72 variations) described in the scientific literature into the SWC standard. The xyz2swc service is available open source through a user-friendly browser interface ( https://neuromorpho.org/xyz2swc/ui/ ) and an Application Programming Interface (API).
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