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Nucleic Acids Res. 2014 Jan;42(2):748-63. doi: 10.1093/nar/gkt917. Epub 2013 Oct 23.

Inference of sigma factor controlled networks by using numerical modeling applied to microarray time series data of the germinating prokaryote.

Author information

1
Laboratory of Bioinformatics, Institute of Microbiology, Academy of Sciences of the Czech Republic, Prague 142 20, Czech Republic.

Abstract

A computational model of gene expression was applied to a novel test set of microarray time series measurements to reveal regulatory interactions between transcriptional regulators represented by 45 sigma factors and the genes expressed during germination of a prokaryote Streptomyces coelicolor. Using microarrays, the first 5.5 h of the process was recorded in 13 time points, which provided a database of gene expression time series on genome-wide scale. The computational modeling of the kinetic relations between the sigma factors, individual genes and genes clustered according to the similarity of their expression kinetics identified kinetically plausible sigma factor-controlled networks. Using genome sequence annotations, functional groups of genes that were predominantly controlled by specific sigma factors were identified. Using external binding data complementing the modeling approach, specific genes involved in the control of the studied process were identified and their function suggested.

PMID:
24157841
PMCID:
PMC3902916
DOI:
10.1093/nar/gkt917
[Indexed for MEDLINE]
Free PMC Article

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