The CoLoMoTo Interactive Notebook relies on Docker and Jupyter technologies to provide a unified environment to edit, execute, share, and reproduce analyses of qualitative models of biological networks.
Quick usage guide
You need Docker and Python. We support GNU/Linux, macOS, and Windows.
sudo pip install -U colomoto-docker # only once; you may have to use pip3 colomoto-docker
The container can be stopped by pressing Ctrl+C keys.
By default, the script will fetch the most recent colomoto/colomoto-docker tag. A specific tag can be specified using the
-V option; or use
-V same to use the most recently fetched image. For example:
colomoto-docker -V 2018-05-29 colomoto-docker -V same # use the most recently downloaded image
Warning: by default, the files within the Docker container are isolated from the running host computer, therefore files are deleted after stopping the container.
To have access to the files of your current directory you should use the
colomoto-docker --bind .
for other options.
Having issues? have a look at our Troubleshooting page, or open an issue.
Available software tools with Python API
- bioLQM – Logical Qualitative Modelling toolkit
- CellCollective – Model repository and knowledge base
- GINsim – Boolean and multi-valued network modelling
- MaBoSS – Markovian Boolean Stochastic Simulator
- NuSMV – Symbolic model-checker
- Pint – Static analyzer for dynamics of Automata Networks
- R-BoolNet – Analysis and reconstruction of Boolean networks dynamics
Generic RPY2 python interface