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Identifying Sources of Variation and the Flow of Information in Biochemical Networks
by Clive Bowsher and Peter Swain
To understand how cells control and exploit biochemical fluctuations,
we must identify the sources of stochasticity, quantify their
effects, and distinguish informative variation from confounding
'noise'. We present an analysis that allows fluctuations of biochemical
networks to be decomposed into multiple components,
gives conditions for the design of experimental reporters to measure
all components, and provides a technique to predict the magnitude
of these components from models. Further, we identify a
particular component of variation that can be used to quantify the
efficacy of information flow through a biochemical network. By applying
our approach to osmosensing in yeast, we can predict the
probability of the different osmotic conditions experienced by wildtype
yeast and show that the majority of variation can be informational
if we include variation generated in response to the cellular
environment. Our results are fundamental to quantifying sources of
variation and thus are a means to understand biological 'design'.
Keywords: analysis of variance; internal history; gene expression;
signal transduction; intrinsic and extrinsic noise.
Full text of the paper (pdf),
which has recently appeared in Proc Natl Acad Sci USA, 2012: 109, E1320. See doi:10.1073/pnas.1119407109
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