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 Language grade: Python 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 3.7 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

Project details


Download files

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

Source Distribution

biomass-0.9.1.tar.gz (124.9 kB view details)

Uploaded Source

Built Distribution

biomass-0.9.1-py3-none-any.whl (163.5 kB view details)

Uploaded Python 3

File details

Details for the file biomass-0.9.1.tar.gz.

File metadata

  • Download URL: biomass-0.9.1.tar.gz
  • Upload date:
  • Size: 124.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.5

File hashes

Hashes for biomass-0.9.1.tar.gz
Algorithm Hash digest
SHA256 e22f84046fbdddd393108c335062b3c90554dfd0757ea8928fe5f5c866788ef7
MD5 e92ab3a003c9e18c88309b5cd82e8893
BLAKE2b-256 351cc4217e1410149ebd91c32a9bd2a86887dd3cdc45f00e3075b842e534b302

See more details on using hashes here.

File details

Details for the file biomass-0.9.1-py3-none-any.whl.

File metadata

  • Download URL: biomass-0.9.1-py3-none-any.whl
  • Upload date:
  • Size: 163.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.5

File hashes

Hashes for biomass-0.9.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4127069124900b0b00545289a615b7dfcafed92ac37f66a6c64271946fd198cd
MD5 fc8f3e397c3a609c82596600892a60b2
BLAKE2b-256 c665a3a930b9f2548e5234b2b1fc6dda14c06b8cc290af83dc953bd1537ec70b

See more details on using hashes here.

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