A computational modelling framework designed to simulate the formation of rosette patterns in tissues of the nervous system.
Project description
neurorosettes
An agent-based framework to model the formation of rosette patterns in tissues of the nervous system
neurorosettes
is a Python package that implements agent-based modelling to study the formation of rosette patterns in tissues
during neuronal development. It is built on top of the vedo
package (version 2022.1.0), which provides an interface
to plot 3D objects using VTK, to prioritize the visualization of the simulations in real time, without requiring additional processing.
Installation
The package can be downloaded through pip using pip install neurorosettes
.
Usage
neurorosettes
offers multiple modules to simulate and test new biological hypothesis, such as:
- Cell cycle and death;
- Creation and extension of neuronal processes;
- Physical interactions between cell bodies and neuronal processes;
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file neurorosettes-0.1.1.tar.gz
.
File metadata
- Download URL: neurorosettes-0.1.1.tar.gz
- Upload date:
- Size: 19.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.1.12 CPython/3.7.15 Windows/10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8d04ecc7907bfce033bd5432e0f4b9b73a464958c6f53ae8d0dce80546fb3bc4 |
|
MD5 | 69c06dfd478338da18d17c5ee51ff217 |
|
BLAKE2b-256 | 51d6affd8e4c4d4b641def3233f14f49c41a39eced7c701799060627ee42e0b1 |
File details
Details for the file neurorosettes-0.1.1-py3-none-any.whl
.
File metadata
- Download URL: neurorosettes-0.1.1-py3-none-any.whl
- Upload date:
- Size: 23.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.1.12 CPython/3.7.15 Windows/10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6aa50e2826273f3c2b96a08782a2fcd5bb90ccb9fcd37fc8ccc687fa72da06f0 |
|
MD5 | 519de57569acf91ce63627d5390bcebc |
|
BLAKE2b-256 | d4823890dc745b54863c2d660f14bd024b2dc2c541b9ae986116e5bea434167b |