title: Stochastic transcriptional regulatory systems with time delays: a mean-field approximation.
abstract: Modeling transcriptional regulation with time delays is an important problem of computational cell biology. In this paper, we propose a computational tool for studying transcriptional regulation in single cells based on a mean-field approximation method. The main idea is to replace the occurrence probabilities of the underlying transcriptional events by their mean values and use appropriately chosen additive noise terms to model statistical variations not accounted by this approximation. The proposed methodology allows us to characterize the transient and steady-state behavior of transcriptional regulation. Moreover, it provides a rather simple and computationally attractive tool for rapid statistical characterization of the dynamic behavior of a nonlinear transcriptional regulatory system with time delays.
authors.affiliation: Whitaker Biomedical Engineering Institute, The Johns Hopkins University, Baltimore, Maryland 21218, USA. goutsias@jhu.edu
authors.forename: John
authors.initials: J
authors.lastname: Goutsias
authors.forename: Seungchan
authors.initials: S
authors.lastname: Kim
mesh_terms: D019295:Computational Biology; D003198:Computer Simulation; D005786:Gene Expression Regulation / Q000235:genetics*; D008957:Models, Genetic; D013269:Stochastic Processes; D014158:Transcription, Genetic / Q000235:genetics*