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Regulatory network operations in the Pathway Tools software.

Paley SM, Latendresse M, Karp PD - BMC Bioinformatics (2012)

Bottom Line: We introduce a novel type of enrichment analysis that asks whether a gene-expression dataset is over-represented for known regulators.We present algorithms for ranking the degree of regulatory influence of genes, and for computing the net positive and negative regulatory influences on a gene.Pathway Tools provides a comprehensive environment for manipulating molecular regulatory interactions that integrates regulatory data with an organism's genome and metabolic network.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bioinformatics Research Group, SRI International 333 Ravenswood Ave, Menlo Park, CA 94025, USA.

ABSTRACT

Background: Biologists are elucidating complex collections of genetic regulatory data for multiple organisms. Software is needed for such regulatory network data.

Results: The Pathway Tools software supports storage and manipulation of regulatory information through a variety of strategies. The Pathway Tools regulation ontology captures transcriptional and translational regulation, substrate-level regulation of enzyme activity, post-translational modifications, and regulatory pathways. Regulatory visualizations include a novel diagram that summarizes all regulatory influences on a gene; a transcription-unit diagram, and an interactive visualization of a full transcriptional regulatory network that can be painted with gene expression data to probe correlations between gene expression and regulatory mechanisms. We introduce a novel type of enrichment analysis that asks whether a gene-expression dataset is over-represented for known regulators. We present algorithms for ranking the degree of regulatory influence of genes, and for computing the net positive and negative regulatory influences on a gene.

Conclusions: Pathway Tools provides a comprehensive environment for manipulating molecular regulatory interactions that integrates regulatory data with an organism's genome and metabolic network. Curated collections of regulatory data authored using Pathway Tools are available for Escherichia coli, Bacillus subtilis, and Shewanella oneidensis.

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The E. coli Cellular Overview diagram. The CRP regulon is highlighted in red, and the IHF regulon is highlighted in green.
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Figure 8: The E. coli Cellular Overview diagram. The CRP regulon is highlighted in red, and the IHF regulon is highlighted in green.

Mentions: The Cellular Overview diagram depicts all pathways and metabolic and transport reactions that occur in an organism, and allows the user to visually explore the metabolic machinery controlled by different regulators. It is shown as a graph in which individual metabolites are the nodes with reactions forming the edges between them, and is organized into sections representing pathway classes. Transport reactions and membrane proteins are depicted around the diagram border, representing the cellular membrane. Various highlighting operations allow for visually querying this diagram — reaction arrows can be colored according to the enzymes (and their corresponding genes) that catalyze them. Several highlighting operations allow visualization of regulatory information (these operations are not yet available on the BioCyc Website, and require local installation of the Pathway Tools software). For example, one operation highlights all reactions whose enzymes are regulated at the substrate level by a specified compound. Another, shown in Figure 8, highlights all reactions whose genes are part of the regulon for (i.e., are regulated by) a specified transcription factor.


Regulatory network operations in the Pathway Tools software.

Paley SM, Latendresse M, Karp PD - BMC Bioinformatics (2012)

The E. coli Cellular Overview diagram. The CRP regulon is highlighted in red, and the IHF regulon is highlighted in green.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3473263&req=5

Figure 8: The E. coli Cellular Overview diagram. The CRP regulon is highlighted in red, and the IHF regulon is highlighted in green.
Mentions: The Cellular Overview diagram depicts all pathways and metabolic and transport reactions that occur in an organism, and allows the user to visually explore the metabolic machinery controlled by different regulators. It is shown as a graph in which individual metabolites are the nodes with reactions forming the edges between them, and is organized into sections representing pathway classes. Transport reactions and membrane proteins are depicted around the diagram border, representing the cellular membrane. Various highlighting operations allow for visually querying this diagram — reaction arrows can be colored according to the enzymes (and their corresponding genes) that catalyze them. Several highlighting operations allow visualization of regulatory information (these operations are not yet available on the BioCyc Website, and require local installation of the Pathway Tools software). For example, one operation highlights all reactions whose enzymes are regulated at the substrate level by a specified compound. Another, shown in Figure 8, highlights all reactions whose genes are part of the regulon for (i.e., are regulated by) a specified transcription factor.

Bottom Line: We introduce a novel type of enrichment analysis that asks whether a gene-expression dataset is over-represented for known regulators.We present algorithms for ranking the degree of regulatory influence of genes, and for computing the net positive and negative regulatory influences on a gene.Pathway Tools provides a comprehensive environment for manipulating molecular regulatory interactions that integrates regulatory data with an organism's genome and metabolic network.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bioinformatics Research Group, SRI International 333 Ravenswood Ave, Menlo Park, CA 94025, USA.

ABSTRACT

Background: Biologists are elucidating complex collections of genetic regulatory data for multiple organisms. Software is needed for such regulatory network data.

Results: The Pathway Tools software supports storage and manipulation of regulatory information through a variety of strategies. The Pathway Tools regulation ontology captures transcriptional and translational regulation, substrate-level regulation of enzyme activity, post-translational modifications, and regulatory pathways. Regulatory visualizations include a novel diagram that summarizes all regulatory influences on a gene; a transcription-unit diagram, and an interactive visualization of a full transcriptional regulatory network that can be painted with gene expression data to probe correlations between gene expression and regulatory mechanisms. We introduce a novel type of enrichment analysis that asks whether a gene-expression dataset is over-represented for known regulators. We present algorithms for ranking the degree of regulatory influence of genes, and for computing the net positive and negative regulatory influences on a gene.

Conclusions: Pathway Tools provides a comprehensive environment for manipulating molecular regulatory interactions that integrates regulatory data with an organism's genome and metabolic network. Curated collections of regulatory data authored using Pathway Tools are available for Escherichia coli, Bacillus subtilis, and Shewanella oneidensis.

Show MeSH
Related in: MedlinePlus