Danish Proteomics Society and Danish Society for Biochemistry and Molecular Biology Symposium, University of Southern Denmark, Odense, Denmark, December 8, 2005

1. Protein interaction networks from yeast to human Lars Juhl Jensen EMBL Heidelberg

2. Current Opinion in Structural Biology, 2005

3. STRING

5. integrate diverse evidence

6. functional interactions

7. Bork et al., Current Opinion in Structural Biology, 2005

8. hundreds of proteomes

9. evolution

12. statistics

13. (the original sin)

14. prokaryotes

15. genomic context methods

16. gene fusion

18. gene neighborhood

20. phylogenetic profiles

25. Cell Cellulosomes Cellulose

26. eukaryotes

27. integrate diverse datasets

28. Jensen et al., Drug Discovery Today: Targets, 2004

29. curated knowledge

30. MIPS Munich Information center for Protein Sequences

31. KEGG Kyoto Encyclopedia of Genes and Genomes

32. STKE Signal Transduction Knowledge Environment

33. Reactome

34. literature mining

35. co-mentioning

36. NLP Natural Language Processing

37. M EDLINE

38. SGD Saccharomyces Genome Database

39. The Interactive Fly

40. OMIM Online Mendelian Inheritance in Man

41. primary experimental data

42. microarray expression data

43. GEO Gene Expression Omnibus

44. physical protein interactions

45. BIND Biomolecular Interaction Network Database

46. MINT Molecular Interactions Database

47. GRID General Repository for Interaction Datasets

48. DIP Database of Interacting Proteins

49. HPRD Human Protein Reference Database

50. problems

51. many sources

52. (different gene identifiers)

53. many types of evidence

54. questionable quality

55. not directly comparable

56. spread over many species

57. huge synonyms lists

58. calculate raw quality scores

59. calibrate vs. gold standard

60. KEGG Kyoto Encyclopedia of Genes and Genomes

61. von Mering et al., Nucleic Acids Research, 2005

62. transfer based on orthology

63. combine all evidence

64. Bork et al., Current Opinion in Structural Biology, 2005

65. Networ-Kin™ Phospho-peptide data (from MS) Predict the kinase class (NetPhosK and Scansite)

66. the human interactome

67. yeast two-hybrid

68. 1936 13 4 4 1385 65 18465 Stelzl et al. Rual et al. Small-scale studies

69. 32 0 3 4 18 4 23 Stelzl et al. Rual et al. Small-scale studies

70. 62 8 39 Small-scale studies Stelzl et al. Rual et al. 852 17 473 432 69 260

71. 3.5% and 21% sensitivity

72. in a couple of years

73. the human interactome

74. 100% = 1/5?

75. the yeast interactome

76. five years ago

77. yeast two-hybrid

78. 1150 117 117 72 4053 118 4469 Uetz et al. Ito et al. Small-scale studies

79. 162 53 34 72 180 29 338 Uetz et al. Ito et al. Small-scale studies

80. 511 189 616 Small-scale studies Uetz et al. Ito et al. 439 178 759 897 190 1347

81. 19% and 12% sensitivity

82. three years ago

83. complex purification and MS

84. 14186 784 1178 287 19492 230 3475 Gavin et al. Ho et al. Small-scale studies

85. 2341 125 656 287 2725 42 149 Gavin et al. Ho et al. Small-scale studies

86. 4431 1465 5041 Small-scale studies Gavin et al. Ho et al. 14913 1071 632 8047 517 746

87. 63% and 41% sensitivity

88. today

89. combining all available data

90. scoring and filtering

92. de Lichtenberg et al., Science, 2005

93. de Lichtenberg et al., Science, 2005

94. de Lichtenberg et al., Science, 2005

95. de Lichtenberg et al., Science, 2005

96. de Lichtenberg et al., Science, 2005

97. the challenge

98. how to get from here …

99. 1936 13 4 4 1385 65 18465 Stelzl et al. Rual et al. Small-scale studies

100. … to there …

101. de Lichtenberg et al., Science, 2005

102. yeast two-hybrid

103. complex purification and MS

104. scoring and filtering

106. Thank you!