A Python package for integrated Boolean and semi-quantitative network modelling.
Tests
| OS \ Python | 3.12 | 3.13 |
|---|---|---|
| Ubuntu | ||
| macOS | ||
| Windows |
Tutorials
tutorial-basic
|
tutorial-advanced
|
For installation, usage, and examples, see the documentation at nib-si.github.io/BoolDog
Bleker, C., Zagorščak, M., Blejec, A., Gruden, K. & Županič, A. BoolDog: integrated Boolean and semi-quantitative network modelling in Python. bioRxiv 10.64898/2026.03.16.711264 (2026).
@article{bleker2026booldog,
title = {BoolDog: integrated Boolean and semi-quantitative network modelling in Python},
author = {Bleker, Carissa and Zagor{\v{s}}{\v{c}}ak, Maja and Blejec, Andrej and Gruden, Kristina and {\v{Z}}upani{\v{c}}, An{\v{z}}e},
journal = {bioRxiv},
year = {2026},
doi = {10.64898/2026.03.16.711264}
}Development version of BoolDog can be installed from GitHub.
To install:
git clone https://github.com/NIB-SI/BoolDog.git
cd BoolDoG
pip install .To install with all optional extras (networks, SBML-qual, BioModels):
pip install .[all]To remove:
pip uninstall booldogA standalone Dockerfile at the repo root builds a container
with BoolDog and its all extras installed. For a container that instead
extends the CoLoMoTo Docker
image (bundled with its own tools and a Jupyter notebook environment), see
colomoto/README.md.
Performance/scalability characterisation of BoolDog runtime against model size and regulatory in-degree is in benchmarks/README.md.
See CONTRIBUTING.md.
