Network biology - Large-scale biomedical data and text mining

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Network biology - Large-scale biomedical data and text mining

  1. 1. Network biologyLarge-scale biomedical data and text mining Lars Juhl Jensen
  2. 2. three parts
  3. 3. one thing in common
  4. 4. guilt by association
  5. 5. Part 1protein networks
  6. 6. Szklarczyk, Franceschini et al., Nucleic Acids Research, 2011
  7. 7. >1100 genomes
  8. 8. genomic context
  9. 9. gene fusion
  10. 10. Korbel et al., Nature Biotechnology, 2004
  11. 11. experimental data
  12. 12. Jensen & Bork, Science, 2008
  13. 13. curated knowledge
  14. 14. Letunic & Bork, Trends in Biochemical Sciences, 2008
  15. 15. many data types
  16. 16. many databases
  17. 17. different formats
  18. 18. different identifiers
  19. 19. variable quality
  20. 20. quality scores
  21. 21. von Mering et al., Nucleic Acids Research, 2005
  22. 22. calibrate vs. gold standard
  23. 23. von Mering et al., Nucleic Acids Research, 2005
  24. 24. orthology transfer
  25. 25. Part 2literature mining
  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. identify the concepts
  33. 33. proteins
  34. 34. compartments
  35. 35. tissues
  36. 36. diseases
  37. 37. comprehensive lexicon
  38. 38. orthographic variation
  39. 39. “black list”
  40. 40. information extraction
  41. 41. co-mentioning
  42. 42. http://diseases.jensenlab.org
  43. 43. abstracts
  44. 44. restricted full-text access
  45. 45. collaborate with publishers
  46. 46. Part 3medical informatics
  47. 47. electronic health records
  48. 48. Jensen et al., Nature Reviews Genetics, 2012
  49. 49. structured data
  50. 50. Jensen et al., Nature Reviews Genetics, 2012
  51. 51. unstructured data
  52. 52. in Danish
  53. 53. by busy doctors
  54. 54. about psychiatric patients
  55. 55. comorbidity
  56. 56. Jensen et al., Nature Reviews Genetics, 2012
  57. 57. multiple testing
  58. 58. Roque et al., PLoS Computational Biology, 2011
  59. 59. patient clustering
  60. 60. Roque et al., PLoS Computational Biology, 2011
  61. 61. cluster characterization
  62. 62. Roque et al., PLoS Computational Biology, 2011
  63. 63. temporal correlation
  64. 64. medication
  65. 65. adverse drug events
  66. 66. pharmacovigilance
  67. 67. AcknowledgmentsSTRING Text mining EPR miningDamian Szklarczyk Sune Frankild Francisco S RoqueAndrea Franceschini Heiko Horn Peter B JensenMichael Kuhn Evangelos Pafilis Robert ErikssonMilan Simonovic Janos Binder Henriette SchmockAlexander Roth Reinhardt Schneider Marlene DalgaardPablo Minguez Sean O’Donoghue Massimo AndreattaTobias Doerks Thomas HansenManuel Stark Karen SøebyJean Muller Søren BredkjærPeer Bork Anders JuulChristian von Mering Thomas Werge Søren Brunak
  68. 68. larsjuhljensen
  69. 69. Thank you

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