Text and data integration

1. Text and data integration
Lars Juhl Jensen

2. interaction networks

3. association networks

4. guilt by association

6. molecular networks

7. STRING

8. protein networks

9. 9.6 million proteins

10. Szklarczyk et al., Nucleic Acids Research, 2015string-db.org

11. STITCH

12. chemical networks

13. 430,000 chemicals

14. Kuhn et al., Nucleic Acids Research, 2014stitch-db.org

15. Exercise 1
Go to http://string-db.org/
Query for human thymidylate
synthase (TYMS) using search by
name
Make sure you are in evidence view
(check the buttons below the
network)
Why are there multiple lines

16. curated knowledge

17. (what we know)

18. text-book material

19. metabolic pathways

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

21. signaling pathways

22. protein complexes

23. 3D structures

25. very incomplete

26. text mining

27. (what we buried)

28. named entity recognition

29. proteins

30. chemicals

31. information extraction

32. co-mentioning

33. counting

34. within documents

35. within paragraphs

36. within sentences

37. scoring scheme

40. NLP
Natural Language Processing

41. experimental data

42. (what we measured)

43. protein interactions

44. Jensen & Bork, Science, 2008

45. genetic interactions

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

47. gene coexpression

49. chemical screens

50. Karaman et al., Nature Biotechnology, 2008

51. predictions

52. (what we infer)

53. genomic context

54. gene fusion

55. Korbel et al., Nature Biotechnology, 2004

56. gene neighborhood

57. Korbel et al., Nature Biotechnology, 2004

58. phylogenetic profiles

59. Korbel et al., Nature Biotechnology, 2004

60. a real example

64. Cell
Cellulosomes
Cellulose

65. Exercise 2
(Continue from where exercise 1
ended)
Which types of evidence support the
interaction between TYMS and
DHFR?
Click on the interaction to view the
popup, which has buttons linking to
full details

66. complications

67. many databases

68. different formats

69. different identifiers

70. variable quality

71. not comparable

72. not same species

73. hard work

74. parsers

75. mapping files

76. quality scores

77. affinity purification

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

79. phylogenetic profiles

81. score calibration

82. gold standard

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

84. implicit weighting by quality

85. common scale

86. homology-based transfer

87. orthologous groups

88. two-step process

89. Franceschini et al., Nucleic Acids Research, 2013

90. Exercise 3
(Continue from where exercise 2
ended)
Change the network to the
confidence view
Change the confidence cutoff to 0.9;
do you see changes in the proteins or
interactions?
Turn off all all evidence types except

91. summary

92. association networks

93. text mining

94. heterogeneous data

95. common identifiers

96. quality scores

97. protein networks

98. Szklarczyk et al., Nucleic Acids Research, 2015string-db.org

99. chemical networks

100. Kuhn et al., Nucleic Acids Research, 2014stitch-db.org

101. COMPARTMENTS

102. subcellular localization

103. Binder et al., Database, 2014compartments.jensenlab.org

104. TISSUES

105. tissue expression

106. tissues.jensenlab.org Santos et al., PeerJ, 2015

107. DISEASES

108. disease associations

109. diseases.jensenlab.org Frankild et al., Methods, 2015

110. Exercise 4
Open http://stitch-db.org
Query for thymidlate synthase (TYMS)
and inspect the TYMS–pemetrexed
interaction
Open http://diseases.jensenlab.org
Search for thymidylate synthase
(TYMS)
What is the strongest associated