Simulation of deterministic and stochastic biochemical reaction networks using Petri Nets
bioPN is a package of C functions that can be used to simulate time-dependent evolution of biochemical reaction networks. The model is defined as a place/transition Petri Net, which is close to how biochemical reactions are defined. The model can be either deterministically solved using an explicit Runge Kutta Dormand Prince 45 method, simulated using four highly optimized variants of the stochastic simulation algorithm, or as a deterministic/stochastic hybrid, according to the Haseltine and Rawlings' algorithm, or using the Partitioned Leaping Algorithm. The library has been optimized for speed and flexibility.
bioPN has been tested only on 64 bits machines, relying on integers of 64 bits. The behavior on 32 bits architectures is untested and not supported.
Roberto Bertolusso and Marek Kimmel
Maintainer: Roberto Bertolusso <email@example.com>
The biological example presented in the functions is extracted from: Paszek, P. (2007) Modeling stochasticity in gene regulation: characterization in the terms of the underlying distribution function, Bull Math Biol, 69, 1567-1601.