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Published June 22, 2020 | Version v0.6.0
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GAlibrate: Model calibration using Genetic Algorithm optimization in Python.

Authors/Creators

  • 1. The University of Texas at Dallas

Description

GAlibrate is a python toolkit that provides an easy-to-use interface for model calibration/parameter estimation using an implementation of continuous genetic algorithm-based optimization. Although GAlibrate provides a general framework for running continuous genetic algorithm-based optimizations, it was created with systems biology models in mind. It therefore supplies additional tools for working with biological models in the PySB format.

Notes

Version 0.6.0 includes: * core GA now returns an array with fitness value of the fittest individual from each generation which can be accessed from the GAO property GAO.best_fitness_per_generation. *Bug fix in core GA for sorting the population before selection and mating.

Files

blakeaw/GAlibrate-v0.6.0.zip

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Additional details

Related works

Is supplement to
https://github.com/blakeaw/GAlibrate/tree/v0.6.0 (URL)