Networks of proteins and diseases

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Networks of proteins and diseases

  1. 1. Networks of proteins and diseases Lars Juhl Jensen
  2. 2. three parts
  3. 3. protein networks
  4. 4. localization and diseases
  5. 5. disease networks
  6. 6. protein networks
  7. 7. STRING
  8. 8. Szklarczyk, Franceschini et al., Nucleic Acids Research, 2011
  9. 9. computational predictions
  10. 10. gene fusion
  11. 11. Korbel et al., Nature Biotechnology, 2004
  12. 12. experimental data
  13. 13. Jensen & Bork, Science, 2008
  14. 14. curated knowledge
  15. 15. Letunic & Bork, Trends in Biochemical Sciences, 2008
  16. 16. many databases
  17. 17. different formats
  18. 18. different identifiers
  19. 19. variable quality
  20. 20. not comparable
  21. 21. hard work
  22. 22. quality scores
  23. 23. von Mering et al., Nucleic Acids Research, 2005
  24. 24. calibrate vs. gold standard
  25. 25. missing most of the data
  26. 26. >10 km
  27. 27. too much to read
  28. 28. computer
  29. 29. as smart as a dog
  30. 30. teach it specific tricks
  31. 31. named entity recognition
  32. 32. comprehensive lexicon
  33. 33. cyclin dependent kinase 1
  34. 34. CDK1
  35. 35. CDC2
  36. 36. orthographic variation
  37. 37. cyclin-dependent kinase 1
  38. 38. hCdc2
  39. 39. “black list”
  40. 40. SDS
  41. 41. information extraction
  42. 42. co-mentioning
  43. 43. localization and disease
  44. 44. proteins
  45. 45. compartments
  46. 46. tissues
  47. 47. diseases
  48. 48. suite of web resources
  49. 49. jensenlab.org
  50. 50. text mining
  51. 51. curated knowledge
  52. 52. experimental data
  53. 53. computational predictions
  54. 54. quality scores
  55. 55. visualization
  56. 56. compartments.jensenlab.org
  57. 57. tissues.jensenlab.org
  58. 58. project onto networks
  59. 59. Szklarczyk, Franceschini et al., Nucleic Acids Research, 2011
  60. 60. compartments.jensenlab.org
  61. 61. tissues.jensenlab.org
  62. 62. diseases.jensenlab.org
  63. 63. disease networks
  64. 64. medical data
  65. 65. electronic health records
  66. 66. Jensen et al., Nature Reviews Genetics, 2012
  67. 67. structured data
  68. 68. Jensen et al., Nature Reviews Genetics, 2012
  69. 69. unstructured data
  70. 70. comorbidity
  71. 71. Jensen et al., Nature Reviews Genetics, 2012
  72. 72. in Danish
  73. 73. multiple testing
  74. 74. confounding factors
  75. 75. age and gender
  76. 76. reporting bias
  77. 77. comorbidity matrix
  78. 78. Roque et al., PLoS Computational Biology, 2011
  79. 79. comorbidity network
  80. 80. temporal correlation
  81. 81. Jensen et al., in preparation, 2012
  82. 82. disease trajectories
  83. 83. Jensen et al., in preparation, 2012
  84. 84. molecular basis
  85. 85. protein networks
  86. 86. AcknowledgmentsSTRING Text EHR miningChristian von MeringDamian Szklarczyk mining Anders Boeck Jensen Peter Bjødstrup Jensen Sune FrankildMichael Kuhn Francisco S. RoqueManuel Stark Evangelos Pafilis Henriette Schmock Janos BinderSamuel Chaffron Marlene DalgaardChris Creevey Kalliopi Tsafou Massimo AndreattaJean Muller Alberto Santos Thomas Hansen Heiko HornTobias Doerks Karen SøebyPhilippe Julien Michael Kuhn Søren Bredkjær Nigel BrownAlexander Roth Anders JuulMilan Simonovic Reinhardt Schneider Tudor OpreaJan Korbel Sean O’Donoghue Pope MoseleyBerend Snel Thomas WergeMartijn Huynen Søren BrunakPeer Bork
  87. 87. Thank you!

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