A Python Framework for Modeling and Analysis of Signaling Systems

biochemical-networks, computational-biology, dynamical-systems, kinetic-modeling, modeling, network-analysis, ode, optimization, ordinary-differential-equations, parameter-estimation, python, simulation, systems-biology, systems-biology-simulation
pip install biomass==0.13.0


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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.


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

$ pip install biomass

BioMASS supports Python 3.8 or newer.


  • 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

  • Arakane, K., Imoto, H., Ormersbach, F. & Okada, M. Extending BioMASS to construct mathematical models from external knowledge. Bioinformatics Advances, vbae042 (2024). https://doi.org/10.1093/bioadv/vbae042


Hiroaki Imoto


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