https://github.com/mattbit/active-network-er

The ER simulation framework provides tools to simulate and analyze motion on network structures which resemble the endoplasmic reticulum.
https://github.com/mattbit/active-network-er

Last synced: 24 days ago
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The ER simulation framework provides tools to simulate and analyze motion on network structures which resemble the endoplasmic reticulum.

• Host: GitHub
• URL: https://github.com/mattbit/active-network-er
• Owner: mattbit
• License: gpl-3.0
• Created: 2020-05-04T13:43:01.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2023-11-09T22:25:25.000Z (over 2 years ago)
• Last Synced: 2025-03-02T16:49:34.365Z (over 1 year ago)
• Language: Python
• Size: 6 MB
• Stars: 0
• Watchers: 2
• Forks: 1
• Open Issues: 3
• Metadata Files:
  • Readme: readme.md
  • License: LICENSE

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README

          
# ER active flow network simulations

[![Build Status](https://travis-ci.com/mattbit/active-network-er.svg?token=zKpBnjBx4d1NEMb7zFbd&branch=master)](https://travis-ci.com/mattbit/active-network-er)

[![GPLv3 license](https://img.shields.io/badge/License-GPLv3-blue.svg)](http://perso.crans.org/besson/LICENSE.html)

[![DOI](https://zenodo.org/badge/261190024.svg)](https://zenodo.org/badge/latestdoi/261190024)

The code provides a framework to implement simulations of particle motion on networks. Different models can be used for the network and the particle behaviour. In particular, the code provides an implementation of the active-flow network model to describe motion on the endoplasmic reticulum.

Some examples of network structures are provided in graphml format in `resources/graphs`.

The code has been tested on Python 3.10.

#### Active-flow network generates molecular transport by packets

The code to reproduce the figures of “Active flow network generates molecular transport by packets” (Proceedings of the Royal Society B, 2020) by Matteo Dora & David Holcman is provided in the `scripts_prsb` subfolder.

Each script will run the required simulations and produce the corresponding figures (it can take some time!). Simulation data and figures will be saved in the locations specified in `config.py`.

The published article can be found [here](https://royalsocietypublishing.org/doi/10.1098/rspb.2020.0493).

### [Documentation](https://mattbit.github.io/active-network-er/)

Documentation can be found [here](https://mattbit.github.io/active-network-er/) or it can be generated with sphinx (look in `docsrc`).

If you have troubles running the code, you have doubts or need any help, don't hesitate to reach out with any question at matteo.dora@ieee.org!

### Development

Development is done using `poetry` to manage dependencies. Tests can be run with python's `unittest` (`$ python -m unittest discover test`) or with `pytest`.

### Authors

The code was written by Matteo Dora (matteo.dora@ieee.org) at the Biology Department of the École Normale Supérieure in Paris as part of his PhD thesis at [David Holcman's lab](https://github.com/holcman-lab).

### License

The code is released under the GPLv3 license (see `LICENSE`).