title: Power graph compression reveals dominant relationships in genetic transcription networks.
abstract: We introduce a framework for the discovery of dominant relationship patterns in transcription networks, by compressing the network into a power graph with overlapping power nodes. Our application of this approach to the transcription networks of S. cerevisiae and E. coli, paired with GO term enrichment analysis, provides a highly informative overview of the most prominent relationships in the gene regulatory networks of these two organisms.
authors: Theory of Condensed Matter Group, Cavendish Laboratory, JJ Thomson Avenue, CB3 0HE Cambridge, UK. sea31@cam.ac.uk.
authors: Sebastian E
authors: SE
authors: Ahnert
mesh_terms: D000465:Algorithms; D004926:Escherichia coli / Q000235:genetics; D015964:Gene Expression Regulation, Bacterial; D015966:Gene Expression Regulation, Fungal; D053263:Gene Regulatory Networks; D008954:Models, Biological; D012441:Saccharomyces cerevisiae / Q000235:genetics; D059467:Transcriptome