The document discusses information integration and association networks. It describes STRING, a database of known and predicted protein-protein interactions that integrates interaction data from genomic context, high-throughput experiments, co-expression and text mining for more than 1100 organisms. STRING generates association networks and scores the confidence of interactions based on different lines of evidence. The document also discusses analyzing cell cycle data using STRING and visualizing networks and external data in Cytoscape.

1. Information integration
Lars Juhl Jensen

6. Part 1
the eukaryotic cell cycle

7. essential process

8. grow and divide

9. one cell

10. two cells

11. four phases

12. G1 phase

13. growth

14. S phase

15. DNA replication

16. G2 phase

17. growth

18. M phase

19. cell division

21. regulation

22. gene expression

23. phosphorylation

24. targeted degradation

25. protein interactions

26. Example 1
my protein and friends

27. http://string-db.org

28. Szklarczyk, Franceschini et al., Nucleic Acids Research, 2011

31. Part 2
association networks

32. guild by association

34. STRING

35. >1100 genomes

36. genomic context

37. gene fusion

38. Korbel et al., Nature Biotechnology, 2004

39. conserved neighborhood

40. Korbel et al., Nature Biotechnology, 2004

41. phylogenetic profiles

42. Korbel et al., Nature Biotechnology, 2004

43. protein interactions

44. Jensen & Bork, Science, 2008

45. genetic interactions

46. Beyer et al., Nature Reviews Genetics, 2007

47. gene coexpression

49. curated knowledge

50. Letunic & Bork, Trends in Biochemical Sciences, 2008

51. >10 km

52. text mining

53. co-mentioning

54. NLP
Natural Language Processing

55. Gene and protein names
Cue words for entity recognition
Verbs for relation extraction
[nxgene The GAL4 gene]
[nxexpr The expression of
[nxgene the cytochrome genes
[nxpg CYC1 and CYC7]]]
is controlled by
[nxpg HAP1]

56. different sources

57. different formats

58. different names

59. not comparable

60. variable quality

61. many parsers

62. comprehensive lexicon

63. quality scores

64. look at the data

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

66. scoring scheme

67. benchmark

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

69. probabilistic scores

70. combine scores

71. Example 2
evidence filters and viewers

74. highest confidence only

76. experiments only

78. evidence viewers

81. Part 3
analysis of cell-cycle data

82. gene expression

83. cell cultures

84. synchronization

85. microarrays

86. time courses

87. look at the data

88. Gauthier et al., Nucleic Acids Research, 2007

89. scoring scheme

90. benchmark

91. time of peak expression

93. protein interactions

94. temporal network

95. de Lichtenberg, Jensen et al., Science, 2005

96. Example 3
a network for my proteins

97. http://string-db.org

100. high confidence only

101. experiments only

103. network expansion

106. Part 4
external data

107. save network

109. open in Cytoscape

110. layout

111. clustering

112. project data onto network

113. de Lichtenberg, Jensen et al., Science, 2005

114. very flexible

115. lose the STRING interface

116. payload mechanism

117. show external data

118. nodes

119. edges

120. hosted on your server

121. Example 4
my data in STRING

122. http://cyclebase-string.jensenlab.org

126. Conclusions

127. know your question

128. collect data

129. look at the data

130. benchmark

132. Thank you!

133. larsjuhljensen