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Network inference from gene expression profiles: what "physical" network are we seeing? (Prokaryotes vs Eukaryotes)
 

Summary: Network inference from gene expression profiles: what "physical"
network are we seeing? (Prokaryotes vs Eukaryotes)
M. Zampieri, N. Soranzo, D. Bianchini and C. Altafini
SISSA-ISAS, International School for Advanced Studies
via Beirut 2-4, 34014 Trieste, Italy
November 14, 2007
Abstract
The concept of reverse engineering a gene network, i.e., of inferring a genome-wide graph
of putative gene-gene interactions from high throughput microarray data has been used ex-
tensively in the last years to deduce/integrate/validate various types of "physical" networks of
interactions among genes or gene products. This paper investigates which of these networks
emerge significantly when reverse engineering collections of gene expression data for two model
organisms, E.coli and S.cerevisiae, without any prior information. For the first organism the
pattern of expression correlations is shown to reflect in fine detail both the operonal struc-
ture of the DNA and post-transcriptional regulatory effects on the gene products, in primis
the co-participation in a protein complex, while for the second organism we find that direct
transcriptional control (e.g., transcription factor binding site interactions) has no statistical
significance and also post-transcriptional regulatory mechanisms (such as co-sharing a protein
complex, colocalization on a metabolic pathway or compartment) are resolved at a lower level
of detail, thereby reflecting the different complexities of the two organisms.

  

Source: Altafini, Claudio - Functional Analysis Sector, Scuola Internazionale Superiore di Studi Avanzati (SISSA)

 

Collections: Engineering; Mathematics