using networks to derive function

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Using networks to derive function Lars Juhl Jensen

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Systems Biology Workshop, Technical University of Denmark, Lyngy, Denmark, May 14-15, 2009

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Page 1: Using networks to derive function

Using networks to derive function

Lars Juhl Jensen

Page 2: Using networks to derive function

STRING

Page 3: Using networks to derive function

Jensen, Kuhn et al., Nucleic Acids Research, 2009

Page 4: Using networks to derive function

functional associations

Page 5: Using networks to derive function

Frishman et al., Modern Genome Annotation, 2009

Page 6: Using networks to derive function

common basis

Page 7: Using networks to derive function

630 genomes

Page 8: Using networks to derive function

model organism databases

Page 9: Using networks to derive function

Ensembl

Page 10: Using networks to derive function

RefSeq

Page 11: Using networks to derive function

genomic context methods

Page 12: Using networks to derive function

gene fusion

Page 13: Using networks to derive function

Korbel et al., Nature Biotechnology, 2004

Page 14: Using networks to derive function

conserved neighborhood

Page 15: Using networks to derive function

operons

Page 16: Using networks to derive function

Korbel et al., Nature Biotechnology, 2004

Page 17: Using networks to derive function

bidirectional promoters

Page 18: Using networks to derive function

Korbel et al., Nature Biotechnology, 2004

Page 19: Using networks to derive function

phylogenetic profiles

Page 20: Using networks to derive function

Korbel et al., Nature Biotechnology, 2004

Page 21: Using networks to derive function

primary experimental data

Page 22: Using networks to derive function

protein interactions

Page 23: Using networks to derive function

yeast two-hybrid

Page 24: Using networks to derive function

affinity purification

Page 25: Using networks to derive function

fragment complementation

Page 26: Using networks to derive function

Jensen & Bork, Science, 2008

Page 27: Using networks to derive function

genetic interactions

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Beyer et al., Nature Reviews Genetics, 2007

Page 29: Using networks to derive function

BINDBiomolecular Interaction Network Database

Page 30: Using networks to derive function

BioGRIDGeneral Repository for Interaction Datasets

Page 31: Using networks to derive function

DIPDatabase of Interacting Proteins

Page 32: Using networks to derive function

IntAct

Page 33: Using networks to derive function

MINTMolecular Interactions Database

Page 34: Using networks to derive function

HPRDHuman Protein Reference Database

Page 35: Using networks to derive function

PDBProtein Data Bank

Page 36: Using networks to derive function

inferred associations

Page 37: Using networks to derive function

gene coexpression

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GEOGene Expression Omnibus

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expression compendia

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curated knowledge

Page 42: Using networks to derive function

complexes

Page 43: Using networks to derive function

MIPSMunich Information center

for Protein Sequences

Page 44: Using networks to derive function

Gene Ontology

Page 45: Using networks to derive function

pathways

Page 46: Using networks to derive function

Letunic & Bork, Trends in Biochemical Sciences, 2008

Page 47: Using networks to derive function

KEGGKyoto Encyclopedia of Genes and Genomes

Page 48: Using networks to derive function

MetaCyc

Page 49: Using networks to derive function

Reactome

Page 50: Using networks to derive function

PIDNCI-Nature Pathway Interaction Database

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literature mining

Page 52: Using networks to derive function

MEDLINE

Page 53: Using networks to derive function

SGDSaccharomyces Genome Database

Page 54: Using networks to derive function

The Interactive Fly

Page 55: Using networks to derive function

OMIMOnline Mendelian Inheritance in Man

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co-mentioning

Page 57: Using networks to derive function

statistical methods

Page 58: Using networks to derive function

NLPNatural Language Processing

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Gene and protein namesCue words for entity recognitionVerbs for relation extraction

[nxgene The GAL4 gene]

[nxexpr The expression of [nxgene the cytochrome genes [nxpg CYC1 and CYC7]]]is controlled by[nxpg HAP1]

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easy in theory …

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… but not in practice

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many data types

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not comparable

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variable quality

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many sources

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different file formats

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different gene identifiers

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partially redundant

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spread over 630 genomes

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quality scores

Page 72: Using networks to derive function

reproducibility

Page 73: Using networks to derive function

von Mering et al., Nucleic Acids Research, 2005

Page 74: Using networks to derive function

benchmarking

Page 75: Using networks to derive function

von Mering et al., Nucleic Acids Research, 2005

Page 76: Using networks to derive function

orthology

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von Mering et al., Nucleic Acids Research, 2005

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two modes

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COG mode

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von Mering et al., Nucleic Acids Research, 2005

Page 81: Using networks to derive function

protein mode

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von Mering et al., Nucleic Acids Research, 2005

Page 83: Using networks to derive function

combine all evidence

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Frishman et al., Modern Genome Annotation, 2009

Page 85: Using networks to derive function

Acknowledgments

Christian von Mering

Michael Kuhn

Manuel Stark

Samuel Chaffron

Philippe Julien

Tobias Doerks

Jan Korbel

Berend Snel

Martijn Huynen

Peer Bork