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
Mechanical Engineering, University of California at Santa Barbara, U.S.A.
Computer Science, University of California at Santa Barbara, U.S.A.
Dan T Gillespie Consulting, Castaic, California, U.S.A.
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