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Proc Natl Acad Sci U S A. 2006 Dec 12;103(50):19033-8. Epub 2006 Nov 30.

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns.

Author information

1
Department of Physics, 104 Davey Laboratory, Pennsylvania State University, University Park, PA 16802, USA.

Abstract

We describe a method based on the principle of entropy maximization to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher-order interactions. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabolic oscillations identifies a gene interaction network that reflects the intracellular communication pathways that adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems.

PMID:
17138668
PMCID:
PMC1748172
DOI:
10.1073/pnas.0609152103
[Indexed for MEDLINE]
Free PMC Article

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