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Characterizing regulatory path motifs in integrated networks using perturbational data.

Joshi A, Van Parys T, Peer YV, Michoel T - Genome Biol. (2010)

Bottom Line: We introduce Pathicular http://bioinformatics.psb.ugent.be/software/details/Pathicular, a Cytoscape plugin for studying the cellular response to perturbations of transcription factors by integrating perturbational expression data with transcriptional, protein-protein and phosphorylation networks.Pathicular searches for 'regulatory path motifs', short paths in the integrated physical networks which occur significantly more often than expected between transcription factors and their targets in the perturbational data.A case study in Saccharomyces cerevisiae identifies eight regulatory path motifs and demonstrates their biological significance.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Plant Systems Biology, VIB, Technologiepark 927, Gent, Belgium. anagha.joshi@psb.vib-ugent.be

ABSTRACT
We introduce Pathicular http://bioinformatics.psb.ugent.be/software/details/Pathicular, a Cytoscape plugin for studying the cellular response to perturbations of transcription factors by integrating perturbational expression data with transcriptional, protein-protein and phosphorylation networks. Pathicular searches for 'regulatory path motifs', short paths in the integrated physical networks which occur significantly more often than expected between transcription factors and their targets in the perturbational data. A case study in Saccharomyces cerevisiae identifies eight regulatory path motifs and demonstrates their biological significance.

Show MeSH
Overlap between transcription factor-target pairs. The overlap between four data sets of transcription factor-target pairs (a) and transcription factors under study (b) showing that there is not a single common transcription factor-target pair inferred by all methods despite 23 common transcription factors.
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Figure 1: Overlap between transcription factor-target pairs. The overlap between four data sets of transcription factor-target pairs (a) and transcription factors under study (b) showing that there is not a single common transcription factor-target pair inferred by all methods despite 23 common transcription factors.

Mentions: In [23], the topological properties of the deletion and overexpression network were compared with a transcriptional network of genome wide ChIP-chip interactions (TRI(C)), assuming that the deletion and overexpression network also consist of direct interactions. We added a fourth transcriptional network to the comparison predicted using cis-regulatory elements (TRI(M)). These four networks contain targets for 23 common transcription factors, but they do not share even a single transcription factor-target pair, although the overlap between each pair of networks is statistically significant (Figure 1). There is much higher overlap between TRI(C) and TRI(M) compared to all other pairwise combinations. On the other hand, the overexpression and deletion networks share only about 2% of their interactions with TRI(C) and TRI(M). This indicates that the deletion and overexpression networks do not contain a large fraction of direct targets.


Characterizing regulatory path motifs in integrated networks using perturbational data.

Joshi A, Van Parys T, Peer YV, Michoel T - Genome Biol. (2010)

Overlap between transcription factor-target pairs. The overlap between four data sets of transcription factor-target pairs (a) and transcription factors under study (b) showing that there is not a single common transcription factor-target pair inferred by all methods despite 23 common transcription factors.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2864572&req=5

Figure 1: Overlap between transcription factor-target pairs. The overlap between four data sets of transcription factor-target pairs (a) and transcription factors under study (b) showing that there is not a single common transcription factor-target pair inferred by all methods despite 23 common transcription factors.
Mentions: In [23], the topological properties of the deletion and overexpression network were compared with a transcriptional network of genome wide ChIP-chip interactions (TRI(C)), assuming that the deletion and overexpression network also consist of direct interactions. We added a fourth transcriptional network to the comparison predicted using cis-regulatory elements (TRI(M)). These four networks contain targets for 23 common transcription factors, but they do not share even a single transcription factor-target pair, although the overlap between each pair of networks is statistically significant (Figure 1). There is much higher overlap between TRI(C) and TRI(M) compared to all other pairwise combinations. On the other hand, the overexpression and deletion networks share only about 2% of their interactions with TRI(C) and TRI(M). This indicates that the deletion and overexpression networks do not contain a large fraction of direct targets.

Bottom Line: We introduce Pathicular http://bioinformatics.psb.ugent.be/software/details/Pathicular, a Cytoscape plugin for studying the cellular response to perturbations of transcription factors by integrating perturbational expression data with transcriptional, protein-protein and phosphorylation networks.Pathicular searches for 'regulatory path motifs', short paths in the integrated physical networks which occur significantly more often than expected between transcription factors and their targets in the perturbational data.A case study in Saccharomyces cerevisiae identifies eight regulatory path motifs and demonstrates their biological significance.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Plant Systems Biology, VIB, Technologiepark 927, Gent, Belgium. anagha.joshi@psb.vib-ugent.be

ABSTRACT
We introduce Pathicular http://bioinformatics.psb.ugent.be/software/details/Pathicular, a Cytoscape plugin for studying the cellular response to perturbations of transcription factors by integrating perturbational expression data with transcriptional, protein-protein and phosphorylation networks. Pathicular searches for 'regulatory path motifs', short paths in the integrated physical networks which occur significantly more often than expected between transcription factors and their targets in the perturbational data. A case study in Saccharomyces cerevisiae identifies eight regulatory path motifs and demonstrates their biological significance.

Show MeSH