Dataset Information
PyPESTO: a modular and scalable tool for parameter estimation for dynamic models.
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ABSTRACT: Summary
Mechanistic models are important tools to describe and understand biological processes. However, they typically rely on unknown parameters, the estimation of which can be challenging for large and complex systems. pyPESTO is a modular framework for systematic parameter estimation, with scalable algorithms for optimization and uncertainty quantification. While tailored to ordinary differential equation problems, pyPESTO is broadly applicable to black-box parameter estimation problems. Besides own implementations, it provides a unified interface to various popular simulation and inference methods.Availability and implementation
pyPESTO is implemented in Python, open-source under a 3-Clause BSD license. Code and documentation are available on GitHub (https://github.com/icb-dcm/pypesto).
SUBMITTER: Schalte Y
PROVIDER: S-EPMC10689677 | biostudies-literature | 2023 Nov
REPOSITORIES: biostudies-literature
Publications
pyPESTO: a modular and scalable tool for parameter estimation for dynamic models.
Bioinformatics (Oxford, England) 20231101 11
<h4>Summary</h4>Mechanistic models are important tools to describe and understand biological processes. However, they typically rely on unknown parameters, the estimation of which can be challenging for large and complex systems. pyPESTO is a modular framework for systematic parameter estimation, with scalable algorithms for optimization and uncertainty quantification. While tailored to ordinary differential equation problems, pyPESTO is broadly applicable to black-box parameter estimation probl ...[more]