Skip to content

eleftherioszisis/TMD

 
 

TMD: Topological Morphology Descriptor

The TMD performs the topological analysis of neuronal morphologies and extracts the persistence barcodes of trees.

©Blue Brain Project/EPFL 2005 – 2019. All rights reserved

Details

Author: Lida Kanari

Contributors: Pawel Dlotko, Benoit Coste

Publication:

A Topological Representation of Branching Neuronal Morphologies

Cite this article as: Kanari, L., Dłotko, P., Scolamiero, M. et al. Neuroinform (2018) 16:3. DOI: https://doi.org/10.1007/s12021-017-9341-1

Related publications:

Comprehensive Morpho-Electrotonic Analysis Shows 2 Distinct Classes of L2 and L3 Pyramidal Neurons in Human Temporal Cortex.

Cite this article as: Deitcher Y., Eyal G., Kanari L., et al. Cerebral Cortex (2017) 27:11 DOI: https://doi.org/10.1093/cercor/bhx226

Objective Classification of Neocortical Pyramidal Cells DOI: http://dx.doi.org/10.1101/349977

Developed in Blue Brain Project

Funding

This project/research was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.

Sotware description

This Python module includes:

  • Basic loading of neuronal morphologies in swc and h5 file format.
  • Extraction of the topological descriptors of tree morphologies.
  • Visualization of neuronal trees and neurons.
  • Ploting persistence diagrams, barcodes and images.

Supported OS

Ubuntu : 12.0, 14.04, 16.04

macOS: Sierra 10.13.3

Required Dependencies

Python : 2.7+

numpy : 1.8.1+, scipy : 0.13.3+, enum34 : 1.0.4+, scikit-learn : 0.19.1+, munkres: 1.0.12+

Optional Dependencies

h5py : 2.8.0+ (optional), matplotlib : 1.3.1+ (required for viewer mode)

Instalation instructions

virtualenv test_tmd
source ./test_tmd/bin/activate
git clone https://github.com/BlueBrain/TMD
pip install ./TMD

For installation of viewers (only works in Python2)

pip install ./TMD[viewer]

Copyright (c) 2016-2021 Blue Brain Project/EPFL

About

No description, website, or topics provided.

Resources

License

Unknown and 2 other licenses found

Licenses found

Unknown
LICENSE.txt
BSD-3-Clause
COPYING-BSD
LGPL-3.0
COPYING-LGPL

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 100.0%