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Mining heterogeneous data: Understanding systems at the level of complexes and networks

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Mining heterogeneous data: Understanding systems at the level of complexes and networks

  1. 1. Mining heterogeneous data Understanding systems at the level of complexes and networks Lars Juhl Jensen
  2. 2. the cell cycle
  3. 3. grow and divide
  4. 4. one cell
  5. 5. two cells
  6. 6. four phases
  7. 7. G 1 phase
  8. 8. growth
  9. 9. S phase
  10. 10. DNA replication
  11. 11. G 2 phase
  12. 12. growth
  13. 13. M phase
  14. 14. cell division
  15. 16. regulation
  16. 17. gene expression
  17. 18. protein complexes
  18. 19. phosphorylation
  19. 20. targeted degradation
  20. 21. gene expression
  21. 22. cell cultures
  22. 23. S. cerevisiae
  23. 25. synchronization
  24. 26. microarrays
  25. 28. time courses
  26. 29. Gauthier et al., Nucleic Acids Research , 2007
  27. 30. cycling genes
  28. 31. scoring scheme
  29. 32. shape
  30. 33. magnitude
  31. 34. benchmarking
  32. 35. Gauthier et al., Nucleic Acids Research , 2007
  33. 36. protein complexes
  34. 37. interaction data
  35. 38. Jensen & Bork, Science , 2008
  36. 39. high error rate
  37. 40. scoring scheme
  38. 41. von Mering et al., Nucleic Acids Research , 2005
  39. 42. von Mering et al., Nucleic Acids Research , 2005
  40. 43. quality threshold
  41. 44. time of peak mRNA level
  42. 45. temporal network
  43. 46. de Lichtenberg, Jensen et al., Science , 2005
  44. 47. hypothesis
  45. 48. just-in-time assembly
  46. 49. de Lichtenberg, Jensen et al., Cell Cycle , 2007
  47. 50. how can we test it?
  48. 51. evolution
  49. 52. microarray time courses
  50. 53. S. pombe
  51. 54. H. sapiens
  52. 55. A. thaliana
  53. 56. cross-species comparison
  54. 57. orthologous genes
  55. 58. sequence similarity
  56. 59. Jensen, Jensen, de Lichtenberg et al., Nature , 2006
  57. 60. protein complexes
  58. 61. all cell-cycle complexes
  59. 62. Jensen, Jensen, de Lichtenberg et al., Nature , 2006
  60. 63. time of peak mRNA level
  61. 64. time of action
  62. 65. just-in-time assembly
  63. 66. pathways
  64. 67. generalize to metabolism
  65. 68. deoxynucleotide synthesis
  66. 70. just-in-time flux
  67. 71. phenotypes
  68. 72. H. sapiens
  69. 73. siRNA screen
  70. 74. comparison with expression
  71. 76. summary
  72. 77. reanalysis
  73. 78. integration
  74. 79. high-throughput data
  75. 80. biological insights
  76. 81. Acknowledgments <ul><li>Thomas Skøt Jensen </li></ul><ul><li>Ulrik de Lichtenberg </li></ul><ul><li>Søren Brunak </li></ul><ul><li>Peer Bork </li></ul>
  77. 82. larsjuhljensen

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