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

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Lars Juhl Jensen

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

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

association networks

guilt by association

protein networks

STRING

2000+ genomes

computational predictions

gene fusion

Korbel et al., Nature Biotechnology, 2004

phylogenetic profiles

Korbel et al., Nature Biotechnology, 2004

experimental data

gene coexpression

physical interactions

Jensen & Bork, Science, 2008

curated knowledge

pathways

Letunic & Bork, Trends in Biochemical Sciences, 2008

many databases

different formats

different identifiers

variable quality

not comparable

hard work

parsers

mapping files

quality scores

von Mering et al., Nucleic Acids Research, 2005

score calibration

gold standard

von Mering et al., Nucleic Acids Research, 2005

common scale

missing most of the data

>10 km

too much to read

computer

as smart as a dog

teach it specific tricks

named entity recognition

comprehensive lexicon

prostate specific antigen

KLK3

orthographic variation

spaces and hyphens

prostate specific antigen

prostate-specific antigen

prefixes and suffixes

KLK3

hKLK3

“black list”

SDS

co-mentioning

within documents

within paragraphs

within sentences

quality score

general approach

protein networks

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

chemical networks

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

localization

subcellular localization

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

tissue expression

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

diseases

associated genes

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

model organisms

Acknowledgments
Molecular networks
Michael Kuhn
Damian Szklarczyk
Andrea Franceschini
Milan Simonovic
Alexander Roth
Sune Pletscher-Frankild
Jianyi Lin
Pablo Minguez
Christian von Mering
Peer Bork
General framework
Sune Pletscher-Frankild
Alberto Santos
Kalliopi Tsafou
Albert Palleja
Evangelos Pafilis
Janos Binder
Christian Stolte
Christos Arvanitidis
Reinhardt Schneider
Sean O’Donoghue

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Dr. E. Muralinath_ Blood indices_clinical aspects

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Molecular markers- RFLP, RAPD, AFLP, SNP etc.

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300003-World Science Day For Peace And Development.pptx

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Exploring Criminology and Criminal Behaviour.pdf

Exploring Criminology and Criminal Behaviour.pdf

Exploring Criminology and Criminal Behaviour.pdf

Bhiwandi Bhiwandi ❤CALL GIRL 7870993772 ❤CALL GIRLS ESCORT SERVICE In Bhiwan...

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Conjugation, transduction and transformation

Conjugation, transduction and transformation

Conjugation, transduction and transformation

GBSN - Microbiology (Unit 3)

GBSN - Microbiology (Unit 3)

GBSN - Microbiology (Unit 3)

PSYCHOSOCIAL NEEDS. in nursing II sem pptx

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Thyroid Physiology_Dr.E. Muralinath_ Associate Professor

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Introduction of DNA analysis in Forensic's .pptx

Introduction of DNA analysis in Forensic's .pptx

Introduction of DNA analysis in Forensic's .pptx

An introduction on sequence tagged site mapping

An introduction on sequence tagged site mapping

An introduction on sequence tagged site mapping

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

4.

5. protein networks

7. 2000+ genomes

8. computational predictions

10. Korbel et al., Nature Biotechnology, 2004

11. phylogenetic profiles

12. Korbel et al., Nature Biotechnology, 2004

13. experimental data

14. gene coexpression

15.

16. physical interactions

17. Jensen & Bork, Science, 2008

18. curated knowledge

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

21. many databases

22. different formats

23. different identifiers

24. variable quality

25. not comparable

28. mapping files

29. quality scores

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

31. score calibration

32. gold standard

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

34. common scale

35. missing most of the data

37. too much to read

39. as smart as a dog

40. teach it specific tricks

41.

42.

43. named entity recognition

44. comprehensive lexicon

45. prostate specific antigen

47. orthographic variation

48. spaces and hyphens

49. prostate specific antigen

50. prostate-specific antigen

51. prefixes and suffixes

54. “black list”

56. co-mentioning

57. within documents

58. within paragraphs

59. within sentences

60. quality score

61. general approach

62. protein networks

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

64. chemical networks

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

66. localization

67. subcellular localization

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

69. tissue expression

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

72. associated genes

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

74. model organisms

75. Acknowledgments Molecular networks Michael Kuhn Damian Szklarczyk Andrea Franceschini Milan Simonovic Alexander Roth Sune Pletscher-Frankild Jianyi Lin Pablo Minguez Christian von Mering Peer Bork General framework Sune Pletscher-Frankild Alberto Santos Kalliopi Tsafou Albert Palleja Evangelos Pafilis Janos Binder Christian Stolte Christos Arvanitidis Reinhardt Schneider Sean O’Donoghue