Skip to main content

Latest release PyPI CI status Test coverage

BioSimulators-BoolNet

BioSimulators-compliant command-line interface to the BoolNet simulation program.

This command-line interface and Docker image enable users to use BoolNet to execute COMBINE/OMEX archives that describe one or more simulation experiments (in SED-ML format) of one or more logical models (in SBML-qual format).

A list of the algorithms and algorithm parameters supported by BoolNet is available at BioSimulators.

A simple web application and web service for using BoolNet to execute COMBINE/OMEX archives is also available at runBioSimulations.

Contents

Installation

Install Python package

pip install biosimulators-boolnet

Install Docker image

docker pull ghcr.io/biosimulators/boolnet

Usage

Local usage

usage: boolnet [-h] [-d] [-q] -i ARCHIVE [-o OUT_DIR] [-v]

BioSimulators-compliant command-line interface to the BoolNet simulation program <https://sysbio.uni-ulm.de/?Software:BoolNet>.

optional arguments:
  -h, --help            show this help message and exit
  -d, --debug           full application debug mode
  -q, --quiet           suppress all console output
  -i ARCHIVE, --archive ARCHIVE
                        Path to OMEX file which contains one or more SED-ML-
                        encoded simulation experiments
  -o OUT_DIR, --out-dir OUT_DIR
                        Directory to save outputs
  -v, --version         show program's version number and exit

Usage through Docker container

The entrypoint to the Docker image supports the same command-line interface described above.

For example, the following command could be used to use the Docker image to execute the COMBINE/OMEX archive ./modeling-study.omex and save its outputs to ./.

docker run \
  --tty \
  --rm \
  --mount type=bind,source="$(pwd)",target=/root/in,readonly \
  --mount type=bind,source="$(pwd)",target=/root/out \
  ghcr.io/biosimulators/boolnet:latest \
    -i /root/in/modeling-study.omex \
    -o /root/out

Documentation

Documentation is available at https://biosimulators.github.io/Biosimulators_BoolNet/.

License

This package is released under the MIT license.

Development team

This package was developed by the Center for Reproducible Biomedical Modeling and the Karr Lab at the Icahn School of Medicine at Mount Sinai in New York.

Questions and comments

Please contact the BioSimulators Team with any questions or comments.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

biosimulators_boolnet-0.1.4.tar.gz (11.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

biosimulators_boolnet-0.1.4-py2.py3-none-any.whl (12.1 kB view details)

Uploaded Python 2Python 3

File details

Details for the file biosimulators_boolnet-0.1.4.tar.gz.

File metadata

  • Download URL: biosimulators_boolnet-0.1.4.tar.gz
  • Upload date:
  • Size: 11.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/54.0.0 requests-toolbelt/0.9.1 tqdm/4.58.0 CPython/3.7.10

File hashes

Hashes for biosimulators_boolnet-0.1.4.tar.gz
Algorithm Hash digest
SHA256 39e73dbc0f9c4bd43d8bc9e69fd41e6dc77925945ade81572d3edb76c549236d
MD5 1b6ed6130ae0716b88194745574e5a21
BLAKE2b-256 bc6da4a7109b2c7fd2f23bfe920081dc445a8433c872b9ac98f5e88066c2e602

See more details on using hashes here.

File details

Details for the file biosimulators_boolnet-0.1.4-py2.py3-none-any.whl.

File metadata

  • Download URL: biosimulators_boolnet-0.1.4-py2.py3-none-any.whl
  • Upload date:
  • Size: 12.1 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/54.0.0 requests-toolbelt/0.9.1 tqdm/4.58.0 CPython/3.7.10

File hashes

Hashes for biosimulators_boolnet-0.1.4-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 9b35b4f1c306a5a0bb63ee1c56c3cefc75cefc598b7392b535711f5d27c40191
MD5 b8b09fb035562d5087bcf2b490b01047
BLAKE2b-256 78f98047c5dd1ca515e230fa42b45c8e98a67c52ba356594f660107c85149613

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page