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BMCBI
2007

Using gene expression data and network topology to detect substantial pathways, clusters and switches during oxygen deprivation

11 years 1 months ago
Using gene expression data and network topology to detect substantial pathways, clusters and switches during oxygen deprivation
Background: Biochemical investigations over the last decades have elucidated an increasingly complete image of the cellular metabolism. To derive a systems view for the regulation of the metabolism when cells adapt to environmental changes, whole genome gene expression profiles can be analysed. Moreover, utilising a network topology based on gene relationships may facilitate interpreting this vast amount of information, and extracting significant patterns within the networks. Results: Interpreting expression levels as pixels with grey value intensities and network topology as relationships between pixels, allows for an image-like representation of cellular metabolism. While the topology of a regular image is a lattice grid, biological networks demonstrate scale-free architecture and thus advanced image processing methods such as wavelet transforms cannot directly be applied. In the study reported here, one-dimensional enzyme-enzyme pairs were tracked to reveal sub-graphs of a biologic...
Gunnar Schramm, Marc Zapatka, Roland Eils, Rainer
Added 12 Dec 2010
Updated 12 Dec 2010
Type Journal
Year 2007
Where BMCBI
Authors Gunnar Schramm, Marc Zapatka, Roland Eils, Rainer König
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