Gene association networks - Large-scale integration of data and text

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This document discusses gene association networks and large-scale data and text integration. It describes how STRING generates association networks from genomic context, gene fusion, coexpression, and curated knowledge from databases. Text mining is used to extract additional associations from the scientific literature, as natural language processing techniques like named entity recognition, information extraction, and semantic tagging are applied to extract gene and protein relationships from text. The extracted information is integrated with experimental interaction data to build comprehensive gene association networks.

Science

Gene association networks
Large-scale integration of data and
text
Lars Juhl Jensen

Korbel et al., Nature Biotechnology, 2004

Letunic & Bork, Trends in Biochemical Sciences, 2008

von Mering et al., Nucleic Acids Research, 2005

Franceschini et al., Nucleic Acids Research, 2013

what you learned in school
pronoun pronoun verb preposition noun

Gene and protein names
Cue words for entity
recognition
Verbs for relation extraction
[nxexpr The expression of
[nxgene the cytochrome
genes
[nxpg CYC1 and CYC7]]]
is controlled by
[nxpg HAP1]
Saric et al., Proceedings of ACL, 2004

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

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

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

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

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

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Gene association networks - Large-scale integration of data and text

1. Gene association networks Large-scale integration of data and text Lars Juhl Jensen

2. association networks

3. guilt by association

7. STRING

10. gene fusion

11. Korbel et al., Nature Biotechnology, 2004

12. gene neighborhood

13. Korbel et al., Nature Biotechnology, 2004

14. phylogenetic profiles

15. Korbel et al., Nature Biotechnology, 2004

16. a real example

17.

18.

19.

20. Cell Cellulosomes Cellulose

21. experimental data

22. gene coexpression

23.

24. physical interactions

25. Jensen & Bork, Science, 2008

26. curated knowledge

27. protein complexes

28.

29. pathways

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

31. many databases

32. different formats

33. different identifiers

34. variable quality

35. not comparable

36. not same species

37. hard work

38. parsers

39. mapping files

40. quality scores

41. affinity purification

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

43. score calibration

44. gold standard

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

46. implicit weighting by quality

47. common scale

48. homology-based transfer

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

50. missing most of the data

51. text mining

52. >10 km

53. too much to read

54. computer

55. as smart as a dog

56. teach it specific tricks

57.

58.

59. named entity recognition

60. comprehensive lexicon

61. cyclin dependent kinase 1

62. CDC2

63. orthographic variation

64. cyclin dependent kinase 1

65. cyclin-dependent kinase 1

66. prefixes and suffixes

67. CDC2

68. hCdc2

69. “black list”

70. SDS

71. information extraction

72. co-mentioning

73. counting

74. within documents

75. within paragraphs

76. within sentences

77. scoring scheme

78.

79.

80. score calibration

81. NLP Natural Language Processing

82. part-of-speech tagging

83. what you learned in school pronoun pronoun verb preposition noun

84. semantic tagging

85. grammatical analysis

86. Gene and protein names Cue words for entity recognition Verbs for relation extraction [nxexpr The expression of [nxgene the cytochrome genes [nxpg CYC1 and CYC7]]] is controlled by [nxpg HAP1] Saric et al., Proceedings of ACL, 2004

87. type and direction

88. complex sentences

89. anaphoric references

90. it

91. general principles

92. gene association network

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

94. STITCH

95. chemical networks

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

97. COMPARTMENTS

98. subcellular localization