Text and data integration
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This document discusses tools for integrating text, data, and various types of evidence to build association networks among proteins, chemicals, and other molecules. It focuses on STRING and STITCH, which aggregate data from curated databases, text mining, and predictions to assign confidence scores and build interactive networks showing functional associations. The exercises guide exploring these resources to learn more about the human thymidylate synthase protein and its interactions.
Text and data integration
- 1. Text and data integration Lars Juhl Jensen
- 7. STRING
- 10. Szklarczyk et al., Nucleic Acids Research, 2015string-db.org
- 11. STITCH
- 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
- 17. (what we know)
- 20. Letunic & Bork, Trends in Biochemical Sciences, 2008
- 23. 3D structures
- 25. very incomplete
- 26. text mining
- 27. (what we buried)
- 29. proteins
- 30. chemicals
- 32. co-mentioning
- 33. counting
- 34. within documents
- 36. within sentences
- 37. scoring scheme
- 44. Jensen & Bork, Science, 2008
- 46. Beyer et al., Nature Reviews Genetics, 2007
- 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
- 57. Korbel et al., Nature Biotechnology, 2004
- 59. Korbel et al., Nature Biotechnology, 2004
- 60. a real example
- 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
- 70. variable quality
- 71. not comparable
- 72. not same species
- 73. hard work
- 74. parsers
- 75. mapping files
- 76. quality scores
- 78. von Mering et al., Nucleic Acids Research, 2005
- 82. gold standard
- 83. von Mering et al., Nucleic Acids Research, 2005
- 84. implicit weighting by quality
- 85. common scale
- 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
- 93. text mining
- 96. quality scores
- 97. protein networks
- 98. Szklarczyk et al., Nucleic Acids Research, 2015string-db.org
- 100. Kuhn et al., Nucleic Acids Research, 2014stitch-db.org
- 101. COMPARTMENTS
- 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