Advanced bioinformatics methods for proteomics

530 views
487 views

Published on

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
530
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
24
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Advanced bioinformatics methods for proteomics

  1. 1. Advanced bioinformaticsmethods for proteomics Lars Juhl Jensen
  2. 2. three parts
  3. 3. signaling networks
  4. 4. association networks
  5. 5. text mining
  6. 6. Part 1signaling networks
  7. 7. phosphoproteomics
  8. 8. Linding, Jensen, Ostheimer et al., Cell, 2007
  9. 9. in vivo phosphosites
  10. 10. kinases are unknown
  11. 11. sequence specificity
  12. 12. Miller, Jensen et al., Science Signaling, 2008
  13. 13. NetPhorest
  14. 14. Miller, Jensen et al., Science Signaling, 2008
  15. 15. motif atlas
  16. 16. kinases
  17. 17. phospho-binding proteins
  18. 18. phosphatases
  19. 19. protein-specific
  20. 20. no context
  21. 21. co-activators
  22. 22. protein scaffolds
  23. 23. localization
  24. 24. expression
  25. 25. association network
  26. 26. Linding, Jensen, Ostheimer et al., Cell, 2007
  27. 27. NetworKIN
  28. 28. Linding, Jensen, Ostheimer et al., Cell, 2007
  29. 29. web interface
  30. 30. Part 2association networks
  31. 31. guilt by association
  32. 32. STRING
  33. 33. Szklarczyk, Franceschini et al., Nucleic Acids Research, 2011
  34. 34. >1100 genomes
  35. 35. computational predictions
  36. 36. genomic context
  37. 37. gene fusion
  38. 38. Korbel et al., Nature Biotechnology, 2004
  39. 39. phylogenetic profiles
  40. 40. Korbel et al., Nature Biotechnology, 2004
  41. 41. experimental data
  42. 42. physical interactions
  43. 43. Jensen & Bork, Science, 2008
  44. 44. gene coexpression
  45. 45. curated knowledge
  46. 46. pathways
  47. 47. Letunic & Bork, Trends in Biochemical Sciences, 2008
  48. 48. many databases
  49. 49. different formats
  50. 50. different identifiers
  51. 51. variable quality
  52. 52. not comparable
  53. 53. quality scores
  54. 54. von Mering et al., Nucleic Acids Research, 2005
  55. 55. calibrate vs. gold standard
  56. 56. von Mering et al., Nucleic Acids Research, 2005
  57. 57. missing most of the data
  58. 58. Part 3text mining
  59. 59. >10 km
  60. 60. too much to read
  61. 61. computer
  62. 62. as smart as a dog
  63. 63. teach it specific tricks
  64. 64. named entity recognition
  65. 65. comprehensive lexicon
  66. 66. proteins
  67. 67. cellular components
  68. 68. compartments.jensenlab.org
  69. 69. tissues
  70. 70. tissues.jensenlab.org
  71. 71. diseases
  72. 72. orthographic variation
  73. 73. singular vs. plural
  74. 74. spaces and hyphens
  75. 75. “black list”
  76. 76. information extraction
  77. 77. co-mentioning
  78. 78. NLPNatural Language Processing
  79. 79. Gene and protein namesCue words for entity recognitionVerbs for relation extraction[nxexpr The expression of [nxgene the cytochrome genes [nxpg CYC1 and CYC7]]] is controlled by [nxpg HAP1]
  80. 80. summary
  81. 81. bioinformatics
  82. 82. more than BLAST
  83. 83. data/text mining
  84. 84. save you much time
  85. 85. AcknowledgmentsNetPhorest NetworKIN STRING Text-Rune LindingMartin Lee Miller Rune Linding Heiko Horn Christian von Mering Damian Szklarczyk miningErwin Schoof Gerard Ostheimer Michael Kuhn Sune FrankildFrancesca Diella Martin Lee Miller Manuel Stark Evangelos PafilisClaus Jørgensen Francesca Diella Samuel Chaffron Janos BinderMichele Tinti Karen Colwill Chris Creevey Heiko HornLei Li Jing Jin Jean Muller Michael KuhnMarilyn Hsiung Pavel Metalnikov Tobias Doerks Nigel BrownSirlester A. Parker Vivian Nguyen Philippe Julien Reinhardt SchneiderJennifer Bordeaux Adrian Pasculescu Alexander Roth Sean O’DonoghueThomas Sicheritz-Pontén Jin Gyoon Park Milan SimonovicMarina Olhovsky Leona D. Samson Jan KorbelAdrian Pasculescu Rob Russell Berend SnelJes Alexander Peer Bork Martijn HuynenStefan Knapp Michael Yaffe Peer BorkNikolaj Blom Tony PawsonPeer BorkShawn LiGianni CesareniTony PawsonBenjamin E. TurkMichael B. YaffeSøren Brunak
  86. 86. larsjuhljensen

×