1. An Exploratory Method to Reconstruct Pathways Cory Tobin

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 Find a better method OR

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 http://www.genome.jp/dbget-bin/get_pathway?org_name=sce&mapno=04110 Our Data

18. Data (cont.) KEGG - Yeast 26S Proteasome Our Data 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