/pyPESTO

python Parameter EStimation TOolbox

Primary LanguagePythonBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

pyPESTO - Parameter EStimation TOolbox for python

pyPESTO logo

pyPESTO is a widely applicable and highly customizable toolbox for parameter estimation.

PyPI CI Coverage Documentation DOI

Feature overview

pyPESTO features include:

  • Multi-start local optimization
  • Profile computation
  • Result visualization
  • Interface to AMICI for efficient simulation and sensitivity analysis of ordinary differential equation (ODE) models (example)
  • Parameter estimation pipeline for systems biology problems specified in SBML and PEtab (example)
  • Parameter estimation with relative (scaled and offset) data as described in Schmiester et al. (2020). (example)
  • Parameter estimation with ordinal data as described in Schmiester et al. (2020) and Schmiester et al. (2021). (example)
  • Parameter estimation with censored data. (example)
  • Parameter estimation with nonlinear-monotone data. (example)

Quick install

The simplest way to install pyPESTO is via pip:

pip3 install pypesto

More information is available here: https://pypesto.readthedocs.io/en/latest/install.html

Documentation

The documentation is hosted on readthedocs.io: https://pypesto.readthedocs.io

Examples

Multiple use cases are discussed in the documentation. In particular, there are jupyter notebooks in the doc/example directory.

Contributing

We are happy about any contributions. For more information on how to contribute to pyPESTO check out https://pypesto.readthedocs.io/en/latest/contribute.html

How to Cite

Citeable DOI for the latest pyPESTO release: DOI

When using pyPESTO in your project, please cite

  • Schälte, Y., Fröhlich, F., Jost, P. J., Vanhoefer, J., Pathirana, D., Stapor, P., Lakrisenko, P., Wang, D., Raimúndez, E., Merkt, S., Schmiester, L., Städter, P., Grein, S., Dudkin, E., Doresic, D., Weindl, D., & Hasenauer, J. (2023). pyPESTO: A modular and scalable tool for parameter estimation for dynamic models, Bioinformatics, 2023, btad711, doi:10.1093/bioinformatics/btad711

When presenting work that employs pyPESTO, feel free to use one of the icons in doc/logo/:

AMICI Logo

There is a list of publications using pyPESTO. If you used pyPESTO in your work, we are happy to include your project, please let us know via a GitHub issue.

References

pyPESTO supersedes PESTO a parameter estimation toolbox for MATLAB, whose development is discontinued.