Title
Aggregation of topological motifs in the Escherichia coli transcriptional regulatory network
Abstract
Transcriptional regulation of cellular functions is carried out through a complex network of interactions among transcription factors and the promoter regions of genes and operons regulated by them. To better understand the system-level function of such networks simplification of their architecture was previously achieved by identifying the motifs present in the network, which are small, overrepresented, topologically distinct regulatory interaction patterns (subgraphs). However, the interaction of such motifs with each other, and their form of integration into the full network has not been previously examined.By studying the transcriptional regulatory network of the bacterium, Escherichia coli, we demonstrate that the two previously identified motif types in the network (i.e., feed-forward loops and bi-fan motifs) do not exist in isolation, but rather aggregate into homologous motif clusters that largely overlap with known biological functions. Moreover, these clusters further coalesce into a supercluster, thus establishing distinct topological hierarchies that show global statistical properties similar to the whole network. Targeted removal of motif links disintegrates the network into small, isolated clusters, while random disruptions of equal number of links do not cause such an effect.Individual motifs aggregate into homologous motif clusters and a supercluster forming the backbone of the E. coli transcriptional regulatory network and play a central role in defining its global topological organization.
Year
DOI
Venue
2004
10.1186/1471-2105-5-10
BMC Bioinformatics
Keywords
Field
DocType
cluster analysis,algorithms,complex network,feed forward,bioinformatics,microarrays,computational biology,transcription regulation,escherichia coli,transcription factor
Transcriptional regulation,Gene,Biology,Operon,Complex network,Bioinformatics,Genetics,Gene regulatory network,Transcription factor,Escherichia coli,DNA microarray
Journal
Volume
Issue
ISSN
5
1
1471-2105
Citations 
PageRank 
References 
52
4.85
2
Authors
4
Name
Order
Citations
PageRank
Radu Dobrin116922.41
Qasim K Beg29810.00
Albert-lászló Barabási346491107.35
Zoltan N Oltvai4738.81