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BIOMD0000000316 - Shen-Orr2002_FeedForward_AND_gate

 

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Reference Publication
Publication ID: 11967538
Shen-Orr SS, Milo R, Mangan S, Alon U.
Network motifs in the transcriptional regulation network of Escherichia coli.
Nat. Genet. 2002 May; 31(1): 64-68
Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.  [more]
Model
Original Model: BIOMD0000000316.origin
Submitter: Kieran Smallbone
Submission ID: MODEL1102140000
Submission Date: 14 Feb 2011 14:40:47 UTC
Last Modification Date: 16 Mar 2011 23:59:41 UTC
Creation Date: 08 Feb 2011 00:00:00 UTC
Encoders:  Kieran Smallbone
set #1
bqbiol:isVersionOf Gene Ontology positive regulation of gene expression
set #2
bqbiol:hasVersion Gene Ontology obsolete transcription activator activity
set #3
bqbiol:hasTaxon Taxonomy Escherichia coli
Notes

This is the coherent feed forward loop with an AND-gate like control of the response operon 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 timecourse presented in Figure 2a. All species and parameters in the model are dimensionless.

Model
Publication ID: 11967538 Submission Date: 14 Feb 2011 14:40:47 UTC Last Modification Date: 16 Mar 2011 23:59:41 UTC Creation Date: 08 Feb 2011 00:00:00 UTC
Mathematical expressions
Reactions
r1 r2 r3 r4
Events
e1 e2 e3 e4
Physical entities
Compartments Species
cell X Y Z
Reactions (4)
 
 r1  ↔ [Y];   {X}
 
 r2 [Y] ↔ ;  
 
 r3  ↔ [Z];   {X} , {Y}
 
 r4 [Z] ↔ ;  
 
Events (4)
 
 e1
X = 1
 
 e2
X = 0
 
 e3
X = 1
 
 e4
X = 0
 
Functions (1)
 
 F lambda(X, T, piecewise(1, X >= T, 0))
 
 cell Spatial dimensions: 3.0  Compartment size: 1.0
 
 X
Compartment: cell
Initial concentration: 0.0
 
 Y
Compartment: cell
Initial concentration: 0.0
 
 Z
Compartment: cell
Initial concentration: 0.0
 
r1 (1)
 
   Ty
Value: 0.5   (Units: dimensionless)
Constant
 
r2 (1)
 
   a
Value: 1.0   (Units: dimensionless)
Constant
 
r3 (2)
 
   Ty
Value: 0.5   (Units: dimensionless)
Constant
 
   Tz
Value: 0.5   (Units: dimensionless)
Constant
 
r4 (1)
 
   a
Value: 1.0   (Units: dimensionless)
Constant
 
Representative curation result(s)
Representative curation result(s) of BIOMD0000000316

Curator's comment: (updated: 20 Feb 2011 23:05:47 GMT)

Time course simulation as in figure 2A of the reference publication, showing that only persistent high levels of X leads to upregulation of Z. The simulation was performed using Copasi 4.6.33.

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