Open AccessListening to the noise: random fluctuations reveal gene network parameters
Author(s) -
Munsky Brian,
Trinh Brooke,
Khammash Mustafa
Publication year - 2009
Publication title -
molecular systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 8.523
H-Index - 148
ISSN - 1744-4292
DOI - 10.1038/msb.2009.75
Subject(s) - biology , noise (video) , identification (biology) , gene regulatory network , stochastic process , biological system , network analysis , gene , computational biology , measure (data warehouse) , statistical physics , genetics , computer science , statistics , physics , data mining , artificial intelligence , mathematics , gene expression , image (mathematics) , botany , quantum mechanics
The cellular environment is abuzz with noise originating from the inherent random motion of reacting molecules in the living cell. In this noisy environment, clonal cell populations show cell‐to‐cell variability that can manifest significant phenotypic differences. Noise‐induced stochastic fluctuations in cellular constituents can be measured and their statistics quantified. We show that these random fluctuations carry within them valuable information about the underlying genetic network. Far from being a nuisance, the ever‐present cellular noise acts as a rich source of excitation that, when processed through a gene network, carries its distinctive fingerprint that encodes a wealth of information about that network. We show that in some cases the analysis of these random fluctuations enables the full identification of network parameters, including those that may otherwise be difficult to measure. This establishes a potentially powerful approach for the identification of gene networks and offers a new window into the workings of these networks.