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An Exploratory Method to Reconstruct Pathways

This project outlines a methodology using Python, PostgreSQL, and Yahoo! Search API to reconstruct signal transduction pathways and protein complexes. By querying protein-protein interactions reported online, the tool constructs high-likelihood queries using joining keywords. Possible solutions for handling large datasets and search hindrances are also discussed, with practical examples provided. The data obtained can be utilized for general reference and database curation, focusing on signal pathways and protein complexes. The project emphasizes generating high-quality data with minimal noise or complex text analysis. References to KEGG, Cytoscape, and Yahoo! Developer Network are included.

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An Exploratory Method to Reconstruct Pathways

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  1. Cory Tobin An Exploratory Method to Reconstruct Pathways

  2. Collaborators Dr. Matteo Pellegrini Shawn Cokus @ UCLA

  3. Outline • Purpose • Methods • Sample Data • Possible Uses • Final Remarks

  4. Purpose Reconstruct signal transduction pathways & protein complexes using protein-protein interactions reported on the web

  5. Materials • Python • Yahoo! Search API • ProstgreSQL • Django Web Framework

  6. Methods Construct high likelihood / low noise queries Ex: “Jak2 phophorylates Stat5” Query Yahoo! for every permutation of 2 proteins in a given species Use high likelihood joining words…

  7. Joining Words Phosphorylates Methylates Acetylates Activates Deactivates Binds to Inhibits Dephosphorylates Glycosylates Ubiquitinates Interacts with

  8. Full Query “Jak2 acetylates OR phosphorylates OR methylates OR binds to OR interacts with Stat5”

  9. Hindrance Doing pair-wise queries for all N proteins in an organism requires N*N queries E. coli has >4000 genes (16,000,000 queries) Yahoo! allows 5k / day / computer

  10. Possible Solutions Recruit 4k computers and finish in a day OR Find a better method

  11. Better Method Only specify the first symbol Iterate through the results and only take results whose word following the joining symbol corresponds to a valid symbol

  12. Full Query “Jak2 acetylates OR phosphorylates OR methylates OR binds to OR interacts with”

  13. Another Hindrance The symbol “thE” (and others like it) Searches need to be case insensitive to account for “p53” and “P53” Recognizes the word “the” as the protein “thE”

  14. Solution Use a list of stop words Very common, non-interesting words If the name appears in that list of stop words, just forget about that protein all together http://www.dcs.gla.ac.uk/idom/ir_resources/linguistic_utils/stop_words

  15. Methods (cont.) After we have this data in a database... Create a web interface to the data so others can search for protein interactions (Shwe)

  16. Data KEGG - Yeast MAPK Our Data http://www.genome.jp/dbget-bin/show_pathway?sce04010+YGR040W

  17. Data (cont.) KEGG - Yeast Cell Cycle Our Data http://www.genome.jp/dbget-bin/get_pathway?org_name=sce&mapno=04110

  18. Data (cont.) Our Data KEGG - Yeast 26S Proteasome http://www.genome.jp/dbget-bin/show_pathway?sce03050+YER012W

  19. Possible Uses • General reference for protein interactions • Curate other databases

  20. Final Remarks • Only works well detecting signal pathways and protein complexes • Not metabolic pathways • It is possible to get high quality, interesting data without much noise or complex text analysis algorithms

  21. References Kyoto Encyclopedia of Genes and Genomes http://www.genome.jp/kegg/ Cytoscape Network Visualization http://www.cytoscape.org/ Yahoo! Developer Network http://developer.yahoo.com/

  22. Acknowledgements • Dr. Matteo Pellegrini • Everyone in the lab • SoCalBSI • NIH / NSF

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