  Steady state is an essential concept in reaction networks. Its stability
reflects fundamental characteristics of several biological phenomena such as
cellular signal transduction and gene expression. Because biochemical reactions
occur at the cellular level, they are affected by unavoidable fluctuations.
Although several methods have been proposed to detect and analyze the stability
of steady states for deterministic models, these methods cannot be applied to
stochastic reaction networks. In this paper, we propose an algorithm based on
algebraic computations to calculate parameter regions for constrained
steady-state distribution of stochastic reaction networks, in which the means
and variances satisfy some given inequality constraints. To evaluate our
proposed method, we perform computer simulations for three typical chemical
reactions and demonstrate that the results obtained with our method are
consistent with the simulation results.
