Biomedical Engineering Reference
In-Depth Information
1.1
NOISE IN GENE REGULATORY
NETWORKS
Juan M. Pedraza and Alexander van Oudenaarden
Department of Physics, Massachusetts Institute of Technology,
Cambridge, Massachusetts
Gene expression is based on biochemical processes that are inherently stochastic. The re-
sulting fluctuations in mRNA and protein levels can sometimes be exploited but gener-
ally need to be controlled for reliable function of regulatory networks. From models of
these biochemical processes it is possible to obtain analytical expressions for the stochas-
tic properties of the resulting distributions of expression levels. We present a review of
the two main analytical techniques for modeling stochastic gene expression.
1.
INTRODUCTION
Noise is often perceived as being undesirable and unpredictable; however,
living systems are inherently noisy, and are optimized to function in the pres-
ence of fluctuations. Biochemical and genetic pathways are sensitive to noise:
some organisms can exploit fluctuations to introduce diversity into a population,
as occurs with the lysis-lysogeny bifurcation in phage M (1,2) or phase variation
in bacteria (3). In contrast, stability against fluctuations is essential for a gene
regulatory cascade controlling cell differentiation in a developing embryo
(4). Robustness to noise can be part of the function of a given network architec-
ture, since structures like feedback loops can be used to reduce noise (5) (see
also preceding chapter 5, Part II, by Krakauer). Stochastic fluctuations in gene
Address correspondence to: Juan M. Pedraza, van Oudenaarden Biophysics Laboratory, Department
of Physics, Room 13-2042, Massachusetts Institute of Technology, Cambridge, Massachusetts
02139-4307 (juan@mit.edu).
211
 
Search WWH ::




Custom Search