1. SpHPP Bioinformatics. 3 rd CHr-16 Workshop. Miraflores de la Sierra December, 10 th -11 th 2012 Alberto Medina

2. Summary 1.Logistics 2.Activities and meetings 3.Data Analysis pipeline 1.Shotgun 2.MRM 4.Sharing data 5.Viewing data 6.Conclusions

3. Summary 1.Logistics 2.Activities and meetings 3.Data Analysis pipeline 1.Shotgun 2.MRM 4.Sharing data 5.Viewing data 6.Conclusions

4. Logistics Logistics: FTP. Public FTP for exchanging “regular” files. A new system should be developed for high throughput instruments. Mailing list. Different lists grouping by working groups Wiki space: http://community.uv.es/mediawiki/http://community.uv.es/mediawiki/ Web site: http://hpp-sp.comhttp://hpp-sp.com Google code site: https://code.google.com/p/s-chpp/ Webex teleconference

5. Website (http://hpp-sp.com)

6. Website. Consortium introduction

7. Website. WG introduction

8. Website. BD page

9. Website CHPP

10. C-HPP Wiki

11. Summary 1.Logistics 2.Activities and meetings 3.Data Analysis pipeline 1.Shotgun 2.MRM 4.Sharing data 5.Viewing data 6.Conclusions

12. Activities and metings 9/3rd: Follow-up teleconference. 9/19th: Follow-up teleconference. 10/3rd: Follow-up teleconference. 10/17th: Follow-up teleconference. 10/31st: Follow-up teleconference. 11/21st: Follow-up teleconference.

13. Summary 1.Logistics 2.Activities and meetings 3.Data Analysis pipeline 1.Shotgun 2.MRM 4.Sharing data 5.Viewing data 6.Conclusions

14. Summary 1.Logistics 2.Activities and meetings 3.Data Analysis pipeline 1.Shotgun 2.MRM 4.Sharing data 5.Viewing data 6.Conclusions

15. Data Analysis Pipeline. Shotgun

17. We are growing!

18. Main improvements Some bugs have been fixed Data Analysis could be directly done by end-users Sequest has been included. Protein Inference – Protein Grouping.

19. Data Analysis. Protein Grouping

20. Main improvements Some bugs have been fixed Data Analysis could be directly done by end-users Sequest has been included. Protein Inference – Protein Grouping. Mascot Server Curated experiments

22. Summary 1.Logistics 2.Activities and meetings 3.Data Analysis pipeline 1.Shotgun 2.MRM 4.Sharing data 5.Viewing data 6.Conclusions

23. Data Analysis. MRM

25. Data Analysis. Proteotipic?

26. Summary 1.Logistics 2.Activities and meetings 3.Data Analysis pipeline 1.Shotgun 2.MRM 4.Sharing data 5.Viewing data 6.Conclusions

27. Sharing Data

30. Summary 1.Logistics 2.Activities and meetings 3.Data Analysis pipeline 1.Shotgun 2.MRM 4.Sharing data 5.Viewing data 6.Conclusions

31. Public Data

32. Viewing Data

35. Viewing other “data”

36. Summary 1.Logistics 2.Activities and meetings 3.Data Analysis pipeline 1.Shotgun 2.MRM 4.Sharing data 5.Viewing data 6.Conclusions

37. Conclusions Website should be filled. WG description ASAP. Continuous activities and meetings. Data Analysis. Shotgun analysis is great! MRM DB Data submission pipeline. Sequest is “active”. Interaction with C-HPP and other chromosomes (TPB).

38. Acknowledges CIMA: Victor Segura Fernando Corrales UCM: Vital Vialas IIBB/CSIC: Óscar Gallardo Ibermática Aitor Moreno UPV: Gorka Prieto Kerman Aloria. Jesús M. Arizmendi. UV: Manuel S. Pino Javi Órtiz CNB/CSIC: Salvador Martínez de Bartolomé. Juan Pablo Albar

39. Discussion Submission pipeline. Protein Inference. Resubmit the data. Sequence BDs. MRM queries. Logo and name.