Current software approaches for stochastic modeling.

implementation uses multi-core parallelism, (1) Maple, (2) Matlab, (3) matplotlib, (4) using converter, (5) if used as plugin for PySCeS [80], method based on the Finite-State Projection algorithm, method based on moment approximation, method based on system size expansion.Existing software packages are divided in groups presenting implementations based on stochastic simulation or such based on the Chemical Master Equation. The software iNA combines both by using the system size expansion which has not been available in a software package yet. In particular, we also list whether the package allows for evaluation of mean concentrations, variances (Var) and the probability density function (PDF).