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An application for parameterization of biological models available in SBML and BNGL formats. Features include parallelization, metaheuristic optimization algorithms, and an adaptive Markov chain Monte Carlo (MCMC) sampling algorithm.

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PyBioNetFit (PyBNF) is a general-purpose program for parameterizing biological models specified using the BioNetGen rule-based modeling language (BNGL) or the Systems Biology Markup Language (SBML). PyBioNetFit offers a suite of parallelized metaheuristic algorithms (differential evolution, particle swarm optimization, scatter search) for parameter optimization. In addition to model parameterization, PyBNF supports uncertainty quantification by bootstrapping or Bayesian approaches, and model checking. PyBNF includes an adaptive Markov chain Monte Carlo (MCMC) sampling algorithm, which supports Bayesian inference. PyBNF includes the Biological Property Specification Language (BPSL) for defining qualitative data for use in parameterization or checking. It runs on most Linux and macOS workstations as well on computing clusters.

For documentation, refer to Documentation_PyBioNetFit.pdf or the online documentation at https://pybnf.readthedocs.io/en/latest/.

PyBioNetFit is released under the BSD-3 license. For more information, refer to the LICENSE. LANL code designation: C18062

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An application for parameterization of biological models available in SBML and BNGL formats. Features include parallelization, metaheuristic optimization algorithms, and an adaptive Markov chain Monte Carlo (MCMC) sampling algorithm.

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