Protein interaction networks from yeast to human

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Danish Proteomics Society and Danish Society for Biochemistry and Molecular Biology Symposium, University of Southern Denmark, Odense, Denmark, December 8, 2005

Transcript of Protein interaction networks from yeast to human

Protein interaction networksfrom yeast to human

Lars Juhl Jensen

EMBL Heidelberg

Current Opinion in Structural Biology, 2005

STRING

integrate diverse evidence

functional interactions

Bork et al., Current Opinion in Structural Biology, 2005

hundreds of proteomes

evolution

statistics

(the original sin)

prokaryotes

genomic context methods

gene fusion

gene neighborhood

phylogenetic profiles

Cell

Cellulosomes

Cellulose

eukaryotes

integrate diverse datasets

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

curated knowledge

MIPSMunich Information center

for Protein Sequences

KEGGKyoto Encyclopedia of Genes and Genomes

STKESignal Transduction Knowledge Environment

Reactome

literature mining

co-mentioning

NLPNatural Language Processing

MEDLINE

SGDSaccharomyces Genome Database

The Interactive Fly

OMIMOnline Mendelian Inheritance in Man

primary experimental data

microarray expression data

GEOGene Expression Omnibus

physical protein interactions

BINDBiomolecular Interaction Network Database

MINTMolecular Interactions Database

GRIDGeneral Repository for Interaction Datasets

DIPDatabase of Interacting Proteins

HPRDHuman Protein Reference Database

problems

many sources

(different gene identifiers)

many types of evidence

questionable quality

not directly comparable

spread over many species

huge synonyms lists

calculate raw quality scores

calibrate vs. gold standard

KEGGKyoto Encyclopedia of Genes and Genomes

von Mering et al., Nucleic Acids Research, 2005

transfer based on orthology

combine all evidence

Bork et al., Current Opinion in Structural Biology, 2005

Networ-Kin™

Phospho-peptidedata (from MS)

Predict the kinase class(NetPhosK and Scansite)

the human interactome

yeast two-hybrid

1936

13

4

4

1385

65

18465

Stelzl et al. Rual et al.

Small-scale studies

32

0

3

4

18

4

23

Stelzl et al. Rual et al.

Small-scale studies

62 8 39

Small-scale studies

Stelzl et al. Rual et al.

852

17

473

432

69

260

3.5% and 21% sensitivity

in a couple of years

the human interactome

100% = 1/5?

the yeast interactome

five years ago

yeast two-hybrid

1150

117

117

72

4053

118

4469

Uetz et al. Ito et al.

Small-scale studies

162

53

34

72

180

29

338

Uetz et al. Ito et al.

Small-scale studies

511 189 616

Small-scale studies

Uetz et al. Ito et al.

439

178

759

897

190

1347

19% and 12% sensitivity

three years ago

complex purification and MS

14186

784

1178

287

19492

230

3475

Gavin et al. Ho et al.

Small-scale studies

2341

125

656

287

2725

42

149

Gavin et al. Ho et al.

Small-scale studies

4431 1465 5041

Small-scale studies

Gavin et al. Ho et al.

14913

1071

632

8047

517

746

63% and 41% sensitivity

today

combining all available data

scoring and filtering

de Lichtenberg et al., Science, 2005

de Lichtenberg et al., Science, 2005

de Lichtenberg et al., Science, 2005

de Lichtenberg et al., Science, 2005

de Lichtenberg et al., Science, 2005

the challenge

how to get from here …

1936

13

4

4

1385

65

18465

Stelzl et al. Rual et al.

Small-scale studies

… to there …

de Lichtenberg et al., Science, 2005

yeast two-hybrid

complex purification and MS

scoring and filtering

Acknowledgments

• The STRING team (EMBL)– Christian von Mering

– Berend Snel

– Martijn Huynen

– Sean Hooper

– Mathilde Foglierini

– Julien Lagarde

– Peer Bork

• Literature mining project(EML Research)– Jasmin Saric

– Rossitza Ouzounova

– Isabel Rojas

• Cell cycle studies (CBS)– Ulrik de Lichtenberg

– Thomas Skøt Jensen

– Søren Brunak

• Networ-Kin™ (Mt. Sinai)– Rune Linding

– Tony Pawson

• Inspiration for presentation– Lawrence Lessig

– Dick Clarence Hardt

– Anders Gorm Pedersen

Thank you!