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SimCluster: pat SimCluster: pat attern recognition attern - PowerPoint PPT Presentation

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Universidade de So Paulo Departamento de Computao o e Matemtica LabPIB - Laboratrio de Processa cessamento de Informao Biolgica Prof. Dr. Vncio rvencio@usp.br SimCluster: pat SimCluster: pat attern recognition attern

  1. Universidade de São Paulo Departamento de Computação o e Matemática LabPIB - Laboratório de Processa cessamento de Informação Biológica Prof. Dr. Vêncio rvencio@usp.br SimCluster: pat SimCluster: pat attern recognition attern recognition for composition nal data

  2. Pattern recognition What do we mean by Pattern Recogn gnition ?

  3. Pattern recognition

  4. Pattern recognition

  5. Pattern recognition

  6. Pattern recognition

  7. Biological motivation Joyce & Palsson, Nat Rev Mol Cell Biol 2006

  8. Biological motivation Joyce & Palsson, Nat Rev Mol Cell Biol 2006

  9. Technological tool to be used: quantit titative sequencing

  10. Technological tool to be used: quantit titative sequencing http://www.genome.gov/sequencingcosts/

  11. Next-gen sequencing Nature Reviews Genetics, 2009

  12. The technical problem we are addres ssing Wang et al. , Nature Reviews Genetics, 2009 9

  13. 2003

  14. Model – the urn model

  15. 2004

  16. 2007

  17. Crucial element in clustering analysis is: distance between objects

  18. Pattern recognition

  19. Model

  20. Crucial element in clustering analysis is: distance between objects

  21. Metric properties

  22. Additional “good” properties for comp positional analysis

  23. Additional “good” properties for comp positional analysis

  24. Additional “good” properties for comp positional analysis

  25. Aitchisonean Distance

  26. Aitchisonean Distance

  27. 2007

  28. Model validation: simulated sequencin cing data from Affymetrix data

  29. Model validation: simulated sequencin cing data from Affymetrix data

  30. Model validation: simulated sequencin cing data from Affymetrix data - mouse macrophages RNA - stimulated by different Toll-like rec ceptor agonists: LPS, PIC, CPG, R848 and PAM - time-course: 0, 20, 40, 60, 80 and 1 120 minutes. - Gilchrist M, et al . Systems biology approaches ident ntify ATF3 as a negative regulator of Toll-like recep eptor 4. Nature 2006, 441:173–178. - Innate Immunity Systems Biology http://www.innateimmunity-system msbiology.org - transcript abundances proportiona al to Affy signal - simulated sampling using real-data ta structure

  31. Model validation: simulated sequencin cing data from Affymetrix data

  32. circumstantial” evidence) � Model validation: other examples (“cir

  33. Web site freely available for all

  34. Opportunities: there is more in Pattern rn Recognition beyond clustering

  35. Opportunities: there is more in Pattern rn Recognition beyond clustering

  36. Opportunities: there is more in Pattern rn Recognition beyond clustering

  37. Acknowledgements Prof. Carlinhos Pro of. Edson Amaro Jr. IME-USP e BIOINFO-USP FM- -USP e HIAE ������������������������� ����

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