Skip to main content

A Python Framework for Modeling and Analysis of Signaling Systems

Project description


PyPI version Actions Status Documentation Status License Downloads PyPI pyversions pre-commit.ci status Code style: black Imports: isort Cancers Paper

BioMASS is a computational framework for modeling and analysis of biological signaling systems in Python.

It provides useful tools for numerical simulation, parameter estimation, network analysis, and result visualization.

Installation

The BioMASS library is available at the Python Package Index (PyPI).

$ pip install biomass

BioMASS supports Python 3.8 or newer.

References

  • Imoto, H., Zhang, S. & Okada, M. A Computational Framework for Prediction and Analysis of Cancer Signaling Dynamics from RNA Sequencing Data—Application to the ErbB Receptor Signaling Pathway. Cancers 12, 2878 (2020). https://doi.org/10.3390/cancers12102878

  • Imoto, H., Yamashiro, S. & Okada, M. A text-based computational framework for patient -specific modeling for classification of cancers. iScience 25, 103944 (2022). https://doi.org/10.1016/j.isci.2022.103944

Author

Hiroaki Imoto

License

Apache License 2.0

Download files

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

Source Distribution

biomass-0.12.0.tar.gz (129.8 kB view hashes)

Uploaded source

Built Distribution

biomass-0.12.0-py3-none-any.whl (164.5 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page