Stochastic binary modeling of cells in continuous time as an alternative to biochemical reaction equations

Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Dec;84(6 Pt 1):062903. doi: 10.1103/PhysRevE.84.062903. Epub 2011 Dec 15.

Abstract

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.

MeSH terms

  • Cell Survival
  • Cells / cytology*
  • Cells / metabolism
  • Markov Chains*
  • Models, Biological*
  • NF-kappa B / metabolism
  • Tumor Necrosis Factor-alpha / metabolism

Substances

  • NF-kappa B
  • Tumor Necrosis Factor-alpha