Simulation of a neuro-epithelium

Vertex model simulation on a toroidal domain, a model for growth and morphogenesis of the developing neural tube.

Python 3 version of this original code. Study published in

Guerrero, P., et al. (2019). Neuronal differentiation influences progenitor arrangement in the vertebrate neuroepithelium. Development, 146(23) https://doi.org/10.1242/dev.176297

Note: the original code presents a bug in the T1 transitions, and this version provides a fix (see below).

Requirements

• Python 3.7.9
• numpy
• matplotlib
• numba
• ...

Installation

It's recommended to setup a conda environment with the above requirements (here called py37)

conda create -n py37 python==3.7.9 numpy matplotlib numba jupyter
conda init $SHELL
conda activate py37

Once you setup your python installation and/or activated your conda environment

git clone https://github.com/berberto/vertex_model.git
cd vertex_model/
pip install -e .

Run

You can test the installation and the functions available with the vertex_model from the jupyter notebook in examples/:

jupyter-notebook examples/example_simulation.ipynb

Main functions

The main functions to look at, in order to see how to set differentiation rates etc, are in vertex_model/run_select.py:

• simulation_with_division
• simulation_with_division_clone
• simulation_with_division_clone_differentiation
• simulation_with_division_clone_differenciation_3stripes

These are the functions to be called for a simulation run. The function run_simulation_INM is a wrapper for these function, and allows to select which of these to be run, along with other options.

Bug fix

The following bug was found in the implementation of the T1 transitions in the original code, resulting in frequently repeating T1 transitions on the same edge. This has been now fixed in function _T1 in mesh.py.

In the images below, orange and blue are (zoom-in of) the mesh configuration respectively before and after the T1 transition.

Old code | New code

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