QPath: A Method for Querying Pathways in a Protein-Protein Interaction Network
Author Information
Author(s): Shlomi Tomer, Segal Daniel, Ruppin Eytan, Sharan Roded
Primary Institution: Tel-Aviv University
Hypothesis
Can pathway homology be used to identify functionally significant pathways?
Conclusion
Pathway homology searches using QPath provide a powerful approach for identifying biologically significant pathways and inferring their function.
Supporting Evidence
- QPath identified 69 conserved pathways whose members were both functionally enriched and coherently expressed.
- 80% of the yeast pathways were functionally enriched.
- 51% of the best-match pathways in fly were functionally enriched.
Takeaway
The study created a tool called QPath that helps scientists find important pathways in proteins by comparing them to known pathways.
Methodology
The QPath algorithm searches for matching pathways composed of distinct proteins that are similar to the query proteins in their sequence and interaction patterns.
Limitations
The study acknowledges the presence of noise in protein interaction data and the challenges of false negatives.
Statistical Information
P-Value
p < 1e-4
Statistical Significance
p < 1e-300
Digital Object Identifier (DOI)
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