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. Here we introduce our formalism and demonstrate it with several examples.
Laboratory of Host Defense, WPI Immunology Frontier Research Center, IFReC, Osaka University, 3-1 Yamada-oka, Suita, Osaka 565-0871, Japan.
Shunsuke
S
Teraguchi
Yutaro
Y
Kumagai
Alexis
A
Vandenbon
Shizuo
S
Akira
Daron M
DM
Standley
D002470:Cell Survival; D002477:Cells / Q000166:cytology* / Q000378:metabolism; D008390:Markov Chains; D008954:Models, Biological; D016328:NF-kappa B / Q000378:metabolism; D014409:Tumor Necrosis Factor-alpha / Q000378:metabolism
D016328:NF-kappa B; D014409:Tumor Necrosis Factor-alpha