This is a repository of data, code and analyses of AstroLogics framework. A step-by step tutorial can be found in the folder tutorial. Please have a look at our tutorials.
AstroLogics is a Python package designed for analysing monotonous Boolean model ensemble, a product of Boolean model synthesis from method such as Bonesis.
Our framework includes two major processes
- Dynamical properties analysis :
- Calculated distance between models through probabilistic approxmition via MaBoSS.
- Logical function evaluation :
- Features logical equation and identify key logical features between model clusters
- Statistical analysis :
- Perform statistical analysis between model clusters to identify key logical featuers between clusters
Overview of the framework showing the two major processes in the framework. Dynamics: dynamical properties analysis. Logics: Logical function evaluation
Statistics: statistical framework to link model's logic with statistics.
- Python version 3.8 or greater
- Python's packages listed here:
- pandas
- numpy
- scipy, sklearn
- maboss
- boolsim
- bonesis
- mpbn
There are several ways to install AstroLogics
pip install astrologics
conda install -c colomoto astrologics
First clone this directory:
git clone https://https://github.com/sysbio-curie/AstroLogics
Then install AstroLogics with pip
pip install AstroLogics
Tutorials are available as Jupyter notebooks
To run this notebook using the built docker image, run :
docker run -p 8888:8888 -d sysbiocurie/astrologics
Creating the conda environment
conda env create --file environment.yml
To activate it :
conda activate astrologics
To run the notebook:
jupyter-lab
Our documentation is available on ReadTheDocs
The manuscript of AstroLogics has been submitted. In the mean time, the pre-print version can be found at https://www.biorxiv.org/content/10.1101/2025.11.17.688236v1