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

Shunsuke Teraguchi, Yutaro Kumagai, Alexis Vandenbon, Shizuo Akira, Daron M. Standley

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

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.

Original languageEnglish
Article number062903
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume84
Issue number6
DOIs
Publication statusPublished - 2011 Dec 15

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Condensed Matter Physics

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