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 month, 2 weeks ago passed

Maintainers

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Tags

workflow, networks, d3, networkx, fmri, nipype, fsl, graph-analysis, connectomics, tractography, brain-connectivity, nilearn, dipy, gaussian-graphical-models, ensemble-sampling, dmri

Short URLs

pynets.readthedocs.io
pynets.rtfd.io

Default Version

latest

'latest' Version

master