Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL Int. J. Robust Nonlinear Control 2005; 15:691711
 

Summary: INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
Int. J. Robust Nonlinear Control 2005; 15:691711
Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/rnc.1018
Stochastic modelling of gene regulatory networks
Hana El Samad1
, Mustafa Khammash1,n,y
, Linda Petzold2
and Dan Gillespie3
1
Mechanical Engineering, University of California at Santa Barbara, U.S.A.
2
Computer Science, University of California at Santa Barbara, U.S.A.
3
Dan T Gillespie Consulting, Castaic, California, U.S.A.
SUMMARY
Gene regulatory networks are dynamic and stochastic in nature, and exhibit exquisite feedback and
feedforward control loops that regulate their biological function at different levels. Modelling of such
networks poses new challenges due, in part, to the small number of molecules involved and the stochastic
nature of their interactions. In this article, we motivate the stochastic modelling of genetic networks and
demonstrate the approach using several examples. We discuss the mathematics of molecular noise models

  

Source: Akhmedov, Azer - Department of Mathematics, University of California at Santa Barbara

 

Collections: Mathematics