Skip to main content

An application for parallel fitting of BioNetGen and SBML models using metaheuristics

Project description

![alt text](docs/Logo1.png “PyBioNetFit”)

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](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](LICENSE). LANL code designation: C18062

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pybnf1.2.1-1.2.0.tar.gz (91.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pybnf1.2.1-1.2.0-py3-none-any.whl (103.9 kB view details)

Uploaded Python 3

File details

Details for the file pybnf1.2.1-1.2.0.tar.gz.

File metadata

  • Download URL: pybnf1.2.1-1.2.0.tar.gz
  • Upload date:
  • Size: 91.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.7

File hashes

Hashes for pybnf1.2.1-1.2.0.tar.gz
Algorithm Hash digest
SHA256 87b1a72d953bd6c1e3d4753383005fc6fbe2522dd3b6450e244e2ca3803b5b64
MD5 9fc6c40bbcb203340bc614bdd488cea8
BLAKE2b-256 6fdb7d8bb62dcbb0ad898facbffb595b456dcd84b4b9049770f62b6c0f61bc53

See more details on using hashes here.

File details

Details for the file pybnf1.2.1-1.2.0-py3-none-any.whl.

File metadata

  • Download URL: pybnf1.2.1-1.2.0-py3-none-any.whl
  • Upload date:
  • Size: 103.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.7

File hashes

Hashes for pybnf1.2.1-1.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 6e2df853e0e5f06381926b6c5fd7194831ec0230ecf43807be3600be67bf1f93
MD5 180b7e4ed24470c7e64cab018eee4ad0
BLAKE2b-256 cb6b5ad004d619d208ee5532c622152196290b279f49ef01e2995e8d3f49c2c2

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page