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Last pushed: 10 days ago
Short Description
The computational systems biology CoLoMoTo notebook
Full Description

The CoLoMoTo Docker

Quick usage guide

You need Docker.
We support GNU/Linux, macOS, and Windows.

Using the colomoto-docker script

You need Python.

The script can be installed and upgraded by executing the following command
(you may have to use pip3 instead of pip depending on your configuration):

pip install -U colomoto-docker

The CoLoMoTo notebook can then be started by executing in a terminal (if using Docker Toolbox, in a Docker Terminal):


The container can be stopped by pressing <kbd>Ctrl</kbd>+<kbd>C</kbd> keys.

By default, the script will fetch the most recent colomoto/colomoto-docker tag. A specific tag can be specified using the -V option. For example:

colomoto-docker -V 2018-05-29

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 --bind option:

colomoto-docker --bind .


colomoto-docker --help

for other options.

Manual invocation

First fetch the image with

docker pull colomoto/colomoto-docker:TAG

where TAG is the version of the image, among colomoto/colomoto-docker tags.

The image can be ran using

docker run -it --rm -p 8888:8888 colomoto/colomoto-docker:TAG

then, open your browser and go to http://localhost:8888 for the Jupyter notebook web interface
(note: when using Docker Toolbox, replace localhost with the result of
docker-machine ip default command).

Embedded software

Besides the Jupyter notebook, the docker image provides
access to the following softwares:

Software tool Homepage Description Jupyter interface
CellCollective Model repository and knowledge base Python module cellcollective
GINsim Boolean and multi-valued network modelling Python module ginsim
bioLQM Logical Qualitative Modelling toolkit Python module biolqm
NuSMV Symbolic model-checker Python module nusmv
Pint Static analyzer for dynamics of Automata Networks Python module pypint
MaBoSS Markovian Boolean Stochastic Simulator Python module maboss

Tagging policy and re-executability considerations

Docker images are timestamped with tags of the form YYYY-MM-DD after each tool addition or upgrade.

In order to guarantee the re-executability of your notebook, we recommend to use these tagged images instead of the non-persistent next tag.



Docker Pull Command
Source Repository