  Molecular noise in gene regulatory networks has two intrinsic components, one
part being due to fluctuations caused by the birth and death of protein or mRNA
molecules which are often present in small numbers and the other part arising
from gene state switching, a single molecule event. Stochastic dynamics of gene
regulatory circuits appears to be largely responsible for bifurcations into a
set of multi-attractor states that encode different cell phenotypes. The
interplay of dichotomous single molecule gene noise with the nonlinear
architecture of genetic networks generates rich and complex phenomena. In this
paper we elaborate on an approximate framework that leads to simple hybrid
multi-scale schemes well suited for the quantitative exploration of the steady
state properties of large-scale cellular genetic circuits.Through a path sum
based analysis of trajectory statistics we elucidate the connection of these
hybrid schemes to the underlying master equation and provide a rigorous
justification for using dichotomous noise based models to study genetic
networks. Numerical simulations of circuit models reveal that the contribution
of the genetic noise of single molecule origin to the total noise is
significant for a wide range of kinetic regimes.
