The STRING database - Quality scores for heterogeneous interaction data

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Lars Juhl Jensen

The document discusses the STRING database, which integrates protein-protein interaction data from numerous sources, including experimental interactions, genomic context methods, co-expression data, and literature mining. It describes the challenges of merging heterogeneous interaction data from various sources in different formats and with different gene identifiers. It also outlines STRING's approach to scoring and combining interactions from multiple data sources, as well as transferring interaction data between species using orthology.

The STRING database Quality scores for heterogeneous interaction data Lars Juhl Jensen EMBL Heidelberg

data integration

Jensen et al., Drug Discovery Today: Targets, 2004

functional interactions

Genomic neighborhood Species co-occurrence Gene fusions Database imports Experimental interaction data Microarray expression data Literature mining

373 proteomes

model organism databases

Ensembl

Genome Reviews

RefSeq

genomic context methods

gene fusion

gene neighborhood

phylogenetic profiles

scoring schemes

benchmarking

cross-species transfer

primary experimental data

many sources

different formats

different gene identifiers

redundancy

physical protein interactions

IntAct

BIND Biomolecular Interaction Network Database

MINT Molecular Interactions Database

DIP Database of Interacting Proteins

GRID General Repository for Interaction Datasets

HPRD Human Protein Reference Database

PSI-MI

reference proteomes

merge data by publication

thousands of interactions

correct interactions

wrong interactions

scoring scheme

complex pull-down

von Mering et al., Nucleic Acids Research, 2005

log[(N 12 · N)/((N 1 +1) · (N 2 +1))]

yeast two-hybrid

non-shared interactors

-log((N 1 +1) · (N 2 +1))

not directly comparable

calibrate vs. gold standard

other types of evidence

co-expression

GEO Gene Expression Omnibus

species-specific datasets

correlation coefficient

calibrate vs. gold standard

directly comparable

curated knowledge

many sources

different formats

different gene identifiers

redundancy

protein complexes

MIPS Munich Information center for Protein Sequences

Gene Ontology

pathway databases

KEGG Kyoto Encyclopedia of Genes and Genomes

Reactome

PID NCI-Nature Pathway Interaction Database

STKE Signal Transduction Knowledge Environment

BioPAX

reference proteomes

literature mining

M EDLINE

SGD Saccharomyces Genome Database

The Interactive Fly

OMIM Online Mendelian Inheritance in Man

different gene identifiers

synonyms lists

black list

flexible matching

co-occurrence

log[(N 12 · N)/((N 1 +1) · (N 2 +1))]

NLP Natural Language Processing

[object Object],[object Object],[object Object],[object Object],[object Object]

calibrate vs. gold standard

directly comparable

combine all evidence

spread over many species

transfer by orthology

von Mering et al., Nucleic Acids Research, 2005

two modes

orthologous groups

von Mering et al., Nucleic Acids Research, 2005

fuzzy orthology

von Mering et al., Nucleic Acids Research, 2005

add probabilistic scores

P = 1-(1-P 1 ) . (1-P 2 ) . (1-P 3 ) …

Genomic neighborhood Species co-occurrence Gene fusions Database imports Experimental interaction data Microarray expression data Literature mining

Acknowledgments ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Discord is a free app offering voice, video, and text chat functionalities, primarily catering to the gaming community. It serves as a hub for users to create and join servers tailored to their interests. Discord’s ecosystem comprises servers, each functioning as a distinct online community with its own channels dedicated to specific topics or activities. Users can engage in text-based discussions, voice calls, or video chats within these channels. Understanding Discord Servers Discord servers are virtual spaces where users congregate to interact, share content, and build communities. Servers may revolve around gaming, hobbies, interests, or fandoms, providing a platform for like-minded individuals to connect. Communication Features Discord offers a range of communication tools, including text channels for messaging, voice channels for real-time audio conversations, and video channels for face-to-face interactions. These features facilitate seamless communication and collaboration. What Does NSFW Mean? The acronym NSFW stands for “Not Safe For Work,” indicating content that may be inappropriate for professional or public settings. NSFW Content NSFW content encompasses material that is sexually explicit, violent, or otherwise graphic in nature. It often includes nudity, profanity, or depictions of sensitive topics.

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The STRING database - Quality scores for heterogeneous interaction data

1. The STRING database Quality scores for heterogeneous interaction data Lars Juhl Jensen EMBL Heidelberg

2. data integration

3. Jensen et al., Drug Discovery Today: Targets, 2004

4. functional interactions

5. Genomic neighborhood Species co-occurrence Gene fusions Database imports Experimental interaction data Microarray expression data Literature mining

6. 373 proteomes

7. model organism databases

9. Genome Reviews

11. genomic context methods

12. gene fusion

13.

14. gene neighborhood

15.

16. phylogenetic profiles

17.

18. scoring schemes

19. benchmarking

20. cross-species transfer

21. primary experimental data

22. many sources

23. different formats

24. different gene identifiers

26. physical protein interactions

28. BIND Biomolecular Interaction Network Database

29. MINT Molecular Interactions Database

30. DIP Database of Interacting Proteins

31. GRID General Repository for Interaction Datasets

32. HPRD Human Protein Reference Database

34. reference proteomes

35. merge data by publication

36. thousands of interactions

37. correct interactions

38. wrong interactions

39. scoring scheme

40. complex pull-down

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

42. log[(N 12 · N)/((N 1 +1) · (N 2 +1))]

43. yeast two-hybrid

44. non-shared interactors

45. -log((N 1 +1) · (N 2 +1))

46. not directly comparable

47. calibrate vs. gold standard

48.

49. other types of evidence

50. co-expression

51. GEO Gene Expression Omnibus

52. species-specific datasets

53. correlation coefficient

54. calibrate vs. gold standard

55. directly comparable

56. curated knowledge

57. many sources

58. different formats

59. different gene identifiers

61. protein complexes

62. MIPS Munich Information center for Protein Sequences

63. Gene Ontology

64. pathway databases

65. KEGG Kyoto Encyclopedia of Genes and Genomes

67. PID NCI-Nature Pathway Interaction Database

68. STKE Signal Transduction Knowledge Environment

70. reference proteomes

71. literature mining

73. SGD Saccharomyces Genome Database

74. The Interactive Fly

75. OMIM Online Mendelian Inheritance in Man

76. different gene identifiers

77. synonyms lists

79. flexible matching

80. co-occurrence

81. log[(N 12 · N)/((N 1 +1) · (N 2 +1))]

82. NLP Natural Language Processing

83.

84. calibrate vs. gold standard

85. directly comparable

86. combine all evidence

87. spread over many species

88. transfer by orthology

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

91.

92. orthologous groups

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

94.

95. fuzzy orthology

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

97. add probabilistic scores

98. P = 1-(1-P 1 ) . (1-P 2 ) . (1-P 3 ) …

99. Genomic neighborhood Species co-occurrence Gene fusions Database imports Experimental interaction data Microarray expression data Literature mining

100.