Large-scale integration of data and text
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This document discusses large-scale integration of biological data and text. It describes combining heterogeneous data from many databases on topics like protein interactions, disease associations, tissue expression, and subcellular localization. It also discusses using text mining of over 10 km of text to extract information on entities, relationships, and annotations in order to supplement incomplete experimental data and facilitate updates and predictions.
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Large-scale integration of data and text
- 1. Large-scale integration of data and text Lars Juhl Jensen
- 7. proteins
- 10. stitch-db.org
- 16. usage statistics
- 17. heavily used
- 19. especially in the US
- 21. data integration
- 26. many databases
- 29. variable quality
- 30. not comparable
- 31. hard work
- 33. quality scores
- 35. missing most of the data
- 36. text mining
- 37. >10 km
- 40. cyclin dependent kinase 1
- 41. CDC2
- 43. hCdc2
- 44. “black list”
- 45. SDS
- 46. co-mentioning
- 47. counting
- 48. within documents
- 50. within sentences
- 53. text mining
- 61. web services
- 63. predictions for dark matter
- 65. questions?