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Rule-based modeling framework
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README.md

bionetgen

Rule-based modeling framework Build Status

BioNetGen is software for the specification and simulation of rule-based models of biochemical systems, including signal transduction, metabolic, and genetic regulatory networks. The BioNetGen language has recently been extended to include explicit representation of compartments. A recent review of methods for rule-based modeling is available in L. A. Chylek et al. (2013) Wiley Interdiscip. Rev. Syst. Biol. Med., 6, 13–36.

BioNetGen is presently a mixture of Perl, C++, and Python. Network generation is currently implemented in Perl, the network simulator is C++, and a new SBML-to-BNGL translator is implemented in Python. In addition, a new language parser is currently being developed in ANTLR.

The BioNetGen software package was initially developed by the Cell Signaling Team at Los Alamos National Laboratory. The current development team is based in the Department of Computational and Systems Biology at the University of Pittsburgh School of Medicine, with contributions from collaborators at the Theoretical Division and Center for Nonlinear Studies at Los Alamos National Laboratory, the Departments of Biology and Computer Science at the University of New Mexico, the Center for Cell Analysis and Modeling at the University of Connecticut Health Center, and the Department of Biological Chemistry at the Johns Hopkins University School of Medicine.

BioNetGen development is currently supported under the auspices of the Center for Multiscale Modeling of Biological Systems (MMBioS), a collaboration between the University of Pittsburgh, the Pittsburgh Supercomputing Center, Carnegie Mellon University, and the Salk Institute (NIH grant P41GM103712). BioNetGen has been supported by NIH grant GM076570 and work has been performed under DOE contract DE-AC52-06NA25396. Additional support for BioNetGen has been provided by NIH grants GM085273, AI35997, and CA109552, NSF grant 0829788, the Arizona Biomedical Research Commission, and the Department of Computational Biology at the University of Pittsburgh School of Medicine.

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