+ Site Statistics
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

Linking stochastic dynamics to population distribution: an analytical framework of gene expression

Linking stochastic dynamics to population distribution: an analytical framework of gene expression

Physical Review Letters 97(16): 168302

We present an analytical framework describing the steady-state distribution of protein concentration in live cells, considering that protein production occurs in random bursts with an exponentially distributed number of molecules. We extend this framework for cases of transcription autoregulation and noise propagation in a simple genetic network. This model allows for the extraction of kinetic parameters of gene expression from steady-state distributions of protein concentration in a cell population, which are available from single cell data obtained by flow cytometry or fluorescence microscopy.

Please choose payment method:

(PDF emailed within 0-6 h: $19.90)

Accession: 049476564

Download citation: RISBibTeXText

PMID: 17155441

DOI: 10.1103/physrevlett.97.168302

Related references

Distribution of population-averaged observables in stochastic gene expression. Physical Review. E Statistical Nonlinear and Soft Matter Physics 89(1): 012715, 2014

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds. Journal of Advances in Modeling Earth Systems 10(2): 448-465, 2018

A framework for predicting species extinction by linking population dynamics with habitat loss. Conservation Letters 5(2): 149-156, 2012

Linking stochastic fluctuations in chromatin structure and gene expression. Plos Biology 11(8): E1001621, 2013

Analytical distributions for stochastic gene expression. Proceedings of the National Academy of Sciences of the United States of America 105(45): 17256-17261, 2008

Analytical approximations for spatial stochastic gene expression in single cells and tissues. Journal of the Royal Society Interface 13(118):, 2016

Time-dependent propagators for stochastic models of gene expression: an analytical method. Journal of Mathematical Biology 77(2): 261-312, 2018

Transcriptional Bursting in Gene Expression: Analytical Results for General Stochastic Models. Plos Computational Biology 11(10): E1004292, 2015

Allelic richness following population founding events--a stochastic modeling framework incorporating gene flow and genetic drift. Plos one 9(12): E115203, 2014

Stochastic processes in population genetics, with special reference to distribution of gene frequencies and probability of gene fixation. Biomathematics. Volume 1. Mathematical topics in population genetics, Berlin, Springer-Verlag, 178-209, 1970

Tsetse population dynamics and distribution: a new analytical approach. Journal of Animal Ecology 483: 825-849, 1979

A flexible modelling framework linking the spatio-temporal dynamics of plant genotypes and populations: Application to gene flow from transgenic forests. Ecological Modelling 202(3-4): 476-486, 2007

Option pricing when correlations are stochastic: an analytical framework. Review of Derivatives Research 10(2): 151-180, 2007

Predicting stochastic gene expression dynamics in single cells. Proceedings of the National Academy of Sciences of the United States of America 103(19): 7304-7309, 2006

The influence of nuclear compartmentalisation on stochastic dynamics of self-repressing gene expression. Journal of Theoretical Biology 424: 55-72, 2017