NFsim is a free, open-source, biochemical reaction simulator designed to handle systems that have a large or even infinite number of possible molecular interactions or states. NFsim also has advanced and flexible options for simulating coarse-grained representations of complex nonlinear reaction mechanisms. A publication describing NFsim can be found here. NFsim is ideal for modeling polymerization, aggregation, and cooperative reactions that cannot be handled with traditional stochastic or ODE simulators. Models are specified in the BioNetGen Langauge, providing a powerful model building environment. Note that you can now develop BioNetGen and NFsim models with a graphical interface in rulebender! NFsim runs on Windows, Mac, and Linux. NFsim code is freely available under the MIT License on github: . Please cite NFsim as: Sneddon MW, Faeder JR and Emonet T. Efficient modeling, simulation and coarse-graining of biological complexity with NFsim. Nature Methods (2011) 8(2):177-83.

References in zbMATH (referenced in 11 articles )

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  1. Troják, Matej; Šafránek, David; Brim, Luboš; Šalagovič, Jakub; Červený, Jan: Executable biochemical space for specification and analysis of biochemical systems (2020)
  2. Cardelli, Luca; Tribastone, Mirco; Tschaikowski, Max; Vandin, Andrea: Symbolic computation of differential equivalences (2019)
  3. Khetan, Jawahar; Barua, Dipak: Analysis of Fn14-NF-(\kappa)B signaling response dynamics using a mechanistic model (2019)
  4. Suderman, Ryan; Mitra, Eshan D.; Lin, Yen Ting; Erickson, Keesha E.; Feng, Song; Hlavacek, William S.: Generalizing Gillespie’s direct method to enable network-free simulations (2019)
  5. Boutillier, Pierre; Ehrhard, Thomas; Krivine, Jean: Incremental update for graph rewriting (2017)
  6. Mohammed, Abdulmelik; Czeizler, Elena; Czeizler, Eugen: Computational modelling of the kinetic tile assembly model using a rule-based approach (2017)
  7. Eftimie, Raluca; Gillard, Joseph J.; Cantrell, Doreen A.: Mathematical models for immunology: current state of the art and future research directions (2016)
  8. Lytton, William W.; Seidenstein, Alexandra H.; Dura-Bernal, Salvador; McDougal, Robert A.; Schürmann, Felix; Hines, Michael L.: Simulation neurotechnologies for advancing brain research: parallelizing large networks in NEURON (2016)
  9. Versari, Cristian; Zavattaro, Gianluigi: Complex functional rates in the modeling of nano devices (extended abstract) (2013) ioport
  10. Danos, Vincent; Koeppl, Heinz; Wilson-Kanamori, John: Cooperative assembly systems (2011)
  11. Pedersen, Michael: A syntactic abstraction for rule-based languages with binding (2011)