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Using networks to derive function Lars Juhl Jensen
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Using networks to derive function

May 10, 2015

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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

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genomic context methods

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gene fusion

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Korbel et al., Nature Biotechnology, 2004

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conserved neighborhood

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operons

Page 16: Using networks to derive function

Korbel et al., Nature Biotechnology, 2004

Page 17: Using networks to derive function

bidirectional promoters

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Korbel et al., Nature Biotechnology, 2004

Page 19: Using networks to derive function

phylogenetic profiles

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Korbel et al., Nature Biotechnology, 2004

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primary experimental data

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protein interactions

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yeast two-hybrid

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affinity purification

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fragment complementation

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Jensen & Bork, Science, 2008

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genetic interactions

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Beyer et al., Nature Reviews Genetics, 2007

Page 29: Using networks to derive function

BINDBiomolecular Interaction Network Database

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BioGRIDGeneral Repository for Interaction Datasets

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DIPDatabase of Interacting Proteins

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IntAct

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MINTMolecular Interactions Database

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HPRDHuman Protein Reference Database

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PDBProtein Data Bank

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inferred associations

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gene coexpression

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GEOGene Expression Omnibus

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expression compendia

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curated knowledge

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complexes

Page 43: Using networks to derive function

MIPSMunich Information center

for Protein Sequences

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Gene Ontology

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pathways

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Letunic & Bork, Trends in Biochemical Sciences, 2008

Page 47: Using networks to derive function

KEGGKyoto Encyclopedia of Genes and Genomes

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MetaCyc

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Reactome

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PIDNCI-Nature Pathway Interaction Database

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literature mining

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MEDLINE

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SGDSaccharomyces Genome Database

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The Interactive Fly

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OMIMOnline Mendelian Inheritance in Man

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co-mentioning

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statistical methods

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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

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reproducibility

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von Mering et al., Nucleic Acids Research, 2005

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benchmarking

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von Mering et al., Nucleic Acids Research, 2005

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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

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protein mode

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von Mering et al., Nucleic Acids Research, 2005

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combine all evidence

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Frishman et al., Modern Genome Annotation, 2009

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Acknowledgments

Christian von Mering

Michael Kuhn

Manuel Stark

Samuel Chaffron

Philippe Julien

Tobias Doerks

Jan Korbel

Berend Snel

Martijn Huynen

Peer Bork