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. S. cerevisiae
  36. 39. Jensen & Bork, Science , 2008
  37. 41. high error rate
  38. 42. scoring scheme
  39. 43. von Mering et al., Nucleic Acids Research , 2005
  40. 44. calibrate against KEGG
  41. 46. quality threshold
  42. 47. temporal network
  43. 48. time of peak mRNA level
  44. 49. time of protein synthesis
  45. 50. de Lichtenberg, Jensen et al., Science , 2005
  46. 51. de Lichtenberg, Jensen et al., Science , 2005
  47. 52. hypothesis
  48. 53. just-in-time assembly
  49. 54. de Lichtenberg, Jensen et al., Cell Cycle , 2007
  50. 55. how can we test it?
  51. 56. evolution
  52. 57. microarray time courses
  53. 58. S. pombe
  54. 59. H. sapiens
  55. 60. A. thaliana
  56. 61. reanalysis
  57. 62. cycling genes
  58. 63. same algorithm
  59. 64. cross-species comparison
  60. 65. orthologous genes
  61. 66. sequence similarity
  62. 67. Jensen, Jensen, de Lichtenberg et al., Nature , 2006
  63. 68. protein complexes
  64. 69. DNA polymerases
  65. 70. Jensen, Jensen, de Lichtenberg et al., Nature , 2006
  66. 71. all cell-cycle complexes
  67. 72. Jensen, Jensen, de Lichtenberg et al., Nature , 2006
  68. 73. time of peak mRNA level
  69. 74. time of action
  70. 75. just-in-time assembly
  71. 76. generalize to metabolism
  72. 77. linear pathways
  73. 78. deoxynucleotide synthesis
  74. 80. just-in-time flux
  75. 81. cell-cycle phenotypes
  76. 82. H. sapiens
  77. 83. siRNA screen
  78. 84. comparison with expression
  79. 86. phosphorylation
  80. 88. CDK substrate
  81. 89. low-throughput data
  82. 90. high-throughput data
  83. 91. NetPhosK
  84. 92. correlation
  85. 93. Jensen, Jensen, de Lichtenberg et al., Nature , 2006
  86. 94. Jensen, Jensen, de Lichtenberg et al., Nature , 2006
  87. 95. bias
  88. 96. correlated changes
  89. 97. Jensen, Jensen, de Lichtenberg et al., Nature , 2006
  90. 98. Jensen, Jensen, de Lichtenberg et al., Nature , 2006
  91. 99. co-evolution
  92. 100. layers of regulation
  93. 101. summary
  94. 102. reanalysis
  95. 103. integration
  96. 104. high-throughput data
  97. 105. biological insights
  98. 106. 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>
  99. 107. larsjuhljensen

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