1. Biomedical text mining
Lars Juhl Jensen

2. exponential growth

5. ~45 seconds per paper

6. information retrieval

7. named entity recognition

8. augmented browsing

9. text corpora

10. information extraction

11. information retrieval

12. find the relevant papers

13. ad hoc retrieval

14. user-specified query

15. “yeast AND cell cycle”

16. PubMed

18. indexing

19. fast lookup

20. stemming

21. word endings

22. dynamic query expansion

23. MeSH terms

24. Mitotic cyclin (Clb2)-bound Cdc28 (Cdk1
homolog) directly phosphorylated Swe1
and this modification served as a priming
step to promote subsequent Cdc5dependent Swe1 hyperphosphorylation
and degradation

25. no tool will find that

26. named entity recognition

27. computer

28. as smart as a dog

29. teach it specific tricks

32. identify the concepts

33. Mitotic cyclin (Clb2)-bound Cdc28 (Cdk1
homolog) directly phosphorylated Swe1
and this modification served as a priming
step to promote subsequent Cdc5dependent Swe1 hyperphosphorylation
and degradation

34. comprehensive lexicon

35. proteins

36. chemicals

37. compartments

38. tissues

39. diseases

40. organisms

41. CDC2

42. cyclin dependent kinase 1

43. orthographic variation

44. upper- and lower-case

45. CDC2

46. Cdc2

47. spaces and hyphens

48. cyclin dependent kinase 1

49. cyclin-dependent kinase 1

50. flexible matching

51. similar to alignment

52. prefixes and postfixes

53. CDC2

54. hCDC2

55. plurals

56. adjectives

57. “black list”

58. SDS

59. efficient tagger

60. Pafilis et al., PLOS ONE, 2013

61. text corpora

62. >10 km
<10 hours

63. most use Medline

64. ~22 million abstracts

65. few use full-text articles

66. no access

67. PDF files

69. layout-aware extraction

70. millions of full-text articles

71. information extraction

72. formalize the facts

73. Mitotic cyclin (Clb2)-bound Cdc28 (Cdk1
homolog) directly phosphorylated Swe1
and this modification served as a priming
step to promote subsequent Cdc5dependent Swe1 hyperphosphorylation
and degradation

74. two approaches

75. co-mentioning

76. counting

77. within documents

78. within paragraphs

79. within sentences

80. co-mentioning score

81. NLP
Natural Language Processing

82. grammatical analysis

83. part-of-speech tagging

84. multiword detection

85. semantic tagging

86. sentence parsing

87. 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]

88. extract stated facts

89. high precision

90. poor recall

91. questions?

92. Exercise 3
Go to http://diseases.jensenlab.org
Find TYMS disease associations
nspect the text-mining evidence
Look for examples of synonym usage
Find genes linked to colorectal cance

93. thank you!