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reaction: 513753
reaction: 513750
created:
  W3 CDTF: Tue Feb 08 00:00:00 GMT 2011
species: 513743
modified:
  W3 CDTF: Thu Mar 17 00:00:23 GMT 2011
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name: Shen-Orr2002_Single_Input_Module
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reaction: 513754
is described by: http://identifiers.org/pubmed/11967538
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    orgname: University of Manchester
  n:
    given: Kieran
    family: Smallbone
reaction: 513749
notes: This is the single input module, SIM, described in the article: Network motifs in the transcriptional regulation network of Escherichia coli Shai S. Shen-Orr, Ron Milo, Shmoolik Mangan, Uri Alon, Nat Genet 2002 31:64-68; PMID: 11967538 ; DOI: 10.1038/ng881 ; Abstract: Little is known about the design principles of transcriptional regulation networks that control gene expression in cells. Recent advances in data collection and analysis, however, are generating unprecedented amounts of information about gene regulation networks. To understand these complex wiring diagrams, we sought to break down such networks into basic building blocks. We generalize the notion of motifs, widely used for sequence analysis, to the level of networks. We define 'network motifs' as patterns of interconnections that recur in many different parts of a network at frequencies much higher than those found in randomized networks. We applied new algorithms for systematically detecting network motifs to one of the best-characterized regulation networks, that of direct transcriptional interactions in Escherichia coli. We find that much of the network is composed of repeated appearances of three highly significant motifs. Each network motif has a specific function in determining gene expression, such as generating temporal expression programs and governing the responses to fluctuating external signals. The motif structure also allows an easily interpretable view of the entire known transcriptional network of the organism. This approach may help define the basic computational elements of other biological networks. This model reproduces the SIM timecourse presented in Figure 2b. All species and parameters in the model are dimensionless.
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