sbioPN
sbioPN: sbioPN: Simulation of deterministic and stochastic spatial biochemical reaction networks using Petri Nets. sbioPN is a package suited to perform simulation of deterministic and stochastic systems of biochemical reaction networks with spatial effects. Models are defined using a subset of Petri Nets, in a way that is close at how chemical reactions are defined. For deterministic solutions, sbioPN creates the associated system of differential equations ”on the fly”, and solves it with a Runge Kutta Dormand Prince 45 explicit algorithm. For stochastic solutions, sbioPN offers two variants of Gillespie algorithm, or SSA. For hybrid deterministic/stochastic, it employs the Haseltine and Rawlings algorithm, that partitions the system in fast and slow reactions. sbioPN algorithms are developed in C to achieve adequate performance.
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References in zbMATH (referenced in 6 articles , 1 standard article )
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Sorted by year (- Du, Yanfei; Wei, Junjie: Bifurcation analysis of a diffusive virus infection and immune response model with two delays (2022)
- Bocharov, G. A.; Volpert, V. A.; Tasevich, A. L.: Reaction-diffusion equations in immunology (2018)
- Marciniak-Czochra, Anna; Härting, Steffen; Karch, Grzegorz; Suzuki, Kanako: Dynamical spike solutions in a nonlocal model of pattern formation (2018)
- Foo, Jasmine; Leder, Kevin; Ryser, Marc D.: Multifocality and recurrence risk: a quantitative model of field cancerization (2014)
- Bertolusso, R.; Kimmel, M.: Modeling spatial effects in early carcinogenesis: stochastic versus deterministic reaction-diffusion systems (2012)
- Bertolusso, Roberto; Kimmel, Marek: Spatial and stochastic effects in a model of viral infection (2012)