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Moreover, utilising a network topology based on gene relationships may facilitate interpreting this vast amount of information, and extracting significant patterns within the networks.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>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 biological interaction network which showed significant adaptations to a changing environment. As a case study, the response of the hetero-fermentative bacterium <jats:italic>E. coli<\/jats:italic> to oxygen deprivation was investigated. With our novel method, we detected, as expected, an up-regulation in the pathways of hexose nutrients up-take and metabolism and formate fermentation. Furthermore, our approach revealed a down-regulation in iron processing as well as the up-regulation of the histidine biosynthesis pathway. The latter may reflect an adaptive response of <jats:italic>E. coli<\/jats:italic> against an increasingly acidic environment due to the excretion of acidic products during anaerobic growth in a batch culture.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>Based on microarray expression profiling data of prokaryotic cells exposed to fundamental treatment changes, our novel technique proved to extract system changes for a rather broad spectrum of the biochemical network.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-8-149","type":"journal-article","created":{"date-parts":[[2007,5,8]],"date-time":"2007-05-08T18:13:27Z","timestamp":1178648007000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Using gene expression data and network topology to detect substantial pathways, clusters and switches during oxygen deprivation of Escherichia coli"],"prefix":"10.1186","volume":"8","author":[{"given":"Gunnar","family":"Schramm","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marc","family":"Zapatka","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roland","family":"Eils","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rainer","family":"K\u00f6nig","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2007,5,8]]},"reference":[{"key":"1521_CR1","volume-title":"Biochemistry","author":"JM Berg","year":"2002","unstructured":"Berg JM, Tymoczko JL, Stryer L: Biochemistry. 5th edition. 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