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.
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.
Documentation can be found here 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 [email protected]!
Development is done using poetry to manage dependencies. Tests can be run with python's unittest ($ python -m unittest discover test) or with pytest.
The code was written by Matteo Dora ([email protected]) at the Biology Department of the École Normale Supérieure in Paris as part of his PhD thesis at David Holcman's lab.
The code is released under the GPLv3 license (see LICENSE).