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 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.

To get started using PyBNF, follow the installation instructions, then look at the examples in the Quick Start.

Contents:

• Installation
  • Operating System
  • Python
  • PyBNF
  • Installation of External Simulators
• Quick Start
  • Verify installation with simple examples
  • Set up your own fitting job
• Configuring a Fitting Job
  • The Configuration File
  • Model Files
  • Experimental Data Files
  • Property (BPSL) files
• Configuration Keys
  • Required Keys
  • Other Path Keys
  • Parameter and Model Specification
  • Simulation Actions
  • Parallel Computing
  • General Options
  • Algorithm-specific Options
• Fitting Algorithms
  • Summary of Available Algorithms
  • General implementation features for all algorithms
  • Differential Evolution
  • Scatter Search
  • Particle Swarm
  • Metropolis-Hastings MCMC
  • Simulated Annealing
  • Parallel Tempering
  • Adaptive MCMC
  • Simplex
• Advanced Features
  • Model Checking
  • Bootstrapping
  • Custom Postprocessing
• Algorithm Development
  • Implementation
  • Adding configuration options
  • Pull requests
• Running on a cluster
  • SLURM
  • TORQUE/PBS
  • Manual configuration with node names
  • Manual configuration with Dask
  • (Optional) Logging configuration for remote machines
• Examples
  • List of examples included in PyBNF
  • Index of examples by attribute
• Troubleshooting
  • Failed simulations
  • Timed out simulations
  • Unexpected behavior when generating SBML files in COPASI
  • Too many open files
  • Too many threads
  • Jobs still running after PyBNF stops
  • PyBNF has encountered a Fatel error
  • An unknown error occurred
  • Other issues

PyBNF Module Reference

Detailed documentation of the PyBNF code base for advanced users

Contents:

• PyBNF Module References
  • PyBNF entry point (pybnf.pybnf)
  • PyBNF algorithms (pybnf.algorithms)
  • PyBNF cluster setup (pybnf.cluster)
  • PyBNF configuration (pybnf.config)
  • PyBNF constraint specification (pybnf.constraint)
  • PyBNF data container (pybnf.data)
  • PyBNF objective functions (pybnf.objective)
  • PyBNF configuration parsing (pybnf.parse)
  • PyBNF printing functions (pybnf.printing)
  • PyBNF model and parameter containers (pybnf.pset)