Stochastic Binary Modeling of Cells in Continuous Time as an Alternative   to Biochemical Reaction Equations
  We have developed a coarse-grained formulation for modeling the dynamic behavior of cells quantitatively, based on stochasticity and heterogeneity, rather than on biochemical reactions. We treat each reaction as a continuous-time stochastic process, while reducing each biochemical quantity to a binary value at the level of individual cells. The system can be analytically represented by a finite set of ordinary linear differential equations, which provides a continuous time course prediction of each molecular state. In this letter, we introduce our formalism and demonstrate it with several examples. 
Shunsuke Teraguchi, Yutaro Kumagai, Alexis Vandenbon, Shizuo Akira and   Daron M Standley
q-bio.MN