Literature DB >> 16624324

A stochastic model of gene transcription: an application to L1 retrotransposition events.

Grzegorz A Rempala1, Kenneth S Ramos, Ted Kalbfleisch.   

Abstract

A simplified mathematical model of gene transcription is presented based on a system of coupled chemical reactions and a corresponding set of stochastic equations similar to those used in enzyme kinetics theory. The quasi-stationary distribution for the model is derived and its usefulness illustrated with an example of model parameters estimation using sparse time course data on L1 retrotransposon expression kinetics. The issue of model validation is also discussed and a simple validation procedure for the estimated model is devised. The procedure compares model predicted values with the laboratory data via the standard Bayesian techniques with the help of modern Markov-Chain Monte-Carlo methodology.

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Year:  2006        PMID: 16624324     DOI: 10.1016/j.jtbi.2006.02.010

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  6 in total

Review 1.  Stochastic modelling for quantitative description of heterogeneous biological systems.

Authors:  Darren J Wilkinson
Journal:  Nat Rev Genet       Date:  2009-02       Impact factor: 53.242

2.  Algebraic methods for inferring biochemical networks: a maximum likelihood approach.

Authors:  Gheorghe Craciun; Casian Pantea; Grzegorz A Rempala
Journal:  Comput Biol Chem       Date:  2009-08-06       Impact factor: 2.877

3.  Bootstrapping least-squares estimates in biochemical reaction networks.

Authors:  Daniel F Linder; Grzegorz A Rempała
Journal:  J Biol Dyn       Date:  2015       Impact factor: 2.179

4.  Comparison of Parameter Estimation Methods in Stochastic Chemical Kinetic Models: Examples in Systems Biology.

Authors:  Ankur Gupta; James B Rawlings
Journal:  AIChE J       Date:  2014-03-05       Impact factor: 3.993

5.  Unraveling genetic regulatory networks of mammalian retroelements.

Authors:  Kenneth S Ramos
Journal:  BMC Proc       Date:  2009-03-10

6.  Incorporating age and delay into models for biophysical systems.

Authors:  Wasiur R KhudaBukhsh; Hye-Won Kang; Eben Kenah; Grzegorz A Rempała
Journal:  Phys Biol       Date:  2021-02-13       Impact factor: 2.959

  6 in total

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