Versions
Description
A Fully-Automated Workflow for Reproducible Ensemble Graph Analysis of Functional and Structural Connectomes PyNets harnesses the power of Nipype, Nilearn, Dipy, and Networkx packages to automatically generate graphical ensembles on a subject-by-subject basis, using virtually any combination of graph hyperparameters. PyNets utilities can be integrated with any existing preprocessing workflow, and a docker container is provided to uniquely facilitate complete reproducibility of executions.
Repository
https://github.com/dPys/PyNets
Project Slug
pynets
Last Built
1 year, 3 months ago passed
Maintainers
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Tags
brain-connectivity, connectomics, d3, dipy, dmri, ensemble-sampling, fmri, fsl, gaussian-graphical-models, graph-analysis, networks, networkx, nilearn, nipype, tractography, workflow
Short URLs
pynets.readthedocs.io
pynets.rtfd.io
Default Version
latest
'latest' Version
master
