Predicting stochastic gene expression dynamics in single cells.

ABSTRACT: Fluctuations in protein numbers (noise) due to inherent stochastic effects in single cells can have large effects on the dynamic behavior of gene regulatory networks. Although deterministic models can predict the average network behavior, they fail to incorporate the stochasticity characteristic of gene expression, thereby limiting their relevance when single cell behaviors deviate from the population average. Recently, stochastic models have been used to predict distributions of steady-state protein levels within a population but not to predict the dynamic, presteady-state distributions. In the present work, we experimentally examine a system whose dynamics are heavily influenced by stochastic effects. We measure population distributions of protein numbers as a function of time in the Esc

SUBMITTER: Mettetal JT 

PROVIDER: S-EPMC1464336 | biostudies-literature | 2006 May

REPOSITORIES: biostudies-literature