Systematic discovery of phosphorylation networks - Combining linear motifs and protein interactions

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Systematic discovery of phosphorylation networks Combining linear motifs and protein interactions Lars Juhl Jensen EMBL Heidelberg

description

Munich, Germany, November 7, 2007

Transcript of Systematic discovery of phosphorylation networks - Combining linear motifs and protein interactions

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Systematic discovery ofphosphorylation networks

Combining linear motifs and protein interactions

Lars Juhl Jensen

EMBL Heidelberg

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Lars Juhl Jensen

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promoter analysis

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genome visualization

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protein function prediction

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data integration

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dynamic interactions

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prediction of interactions

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http://string.embl.de

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prediction of interactions

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http://networkin.info

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the starting point

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phosphoproteomics

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mass spectrometry

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phosphorylation sites

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in vivo

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kinases are unknown

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HTP kinase assays

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in vitro

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no context

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what a kinase could do

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not what it actually does

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computational methods

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sequence motifs

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kinase families

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phosphorylation sites

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overprediction

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no context

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what a kinase could do

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not what it actually does

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in vitro

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in vivo

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context

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localization

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expression

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co-activators

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scaffolders

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protein networks

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the idea

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mass spectrometry

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phosphorylation sites

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sequence motifs

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kinase families

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protein networks

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context

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in vitro

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in vivo

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“shake and bake”

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NetworKIN

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the context network

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STRING

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functional interactions

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373 genomes

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genomic context methods

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gene neighborhood

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gene fusion

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phylogenetic profiles

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primary experimental data

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protein interactions

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genetic interactions

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gene coexpression

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literature mining

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curated knowledge

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many sources

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different formats

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different gene identifiers

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redundancy

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variable quality

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spread over many species

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benchmarking

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transfer by orthology

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combine all evidence

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the results

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7797 predictions

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1790 substrates

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69 kinases

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benchmarking

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Phospho.ELM

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2.5-fold better accuracy

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context is crucial

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localization

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visualization

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ATM signaling

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small-scale validation

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ATM phosphorylates Rad50

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Cdk1 phosphorylates 53BP1

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high-throughput validation

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multiple reaction monitoring

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the future

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more sequence motifs

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in vivo

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in vitro

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automatic pipeline

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http://netphorest.info

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data organization

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benchmarking

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selection

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179 kinases

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89 SH2 domains

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8 PTB domains

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upstream signaling

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downstream signaling

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ordered signaling events

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signaling pathways

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Acknowledgments

The NetworKIN method– Rune Linding

– Gerard Ostheimer

– Francesca Diella

– Karen Colwill

– Jing Jin

– Pavel Metalnikov

– Vivian Nguyen

– Adrian Pasculescu

– Jin Gyoon Park

– Leona D. Samson

– Rob Russell

– Peer Bork

– Michael Yaffe

– Tony Pawson

The STRING database– Christian von Mering

– Michael Kuhn

– Berend Snel

– Martijn Huynen

– Samuel Chaffron

– Peer Bork

• The NetPhorest method– Martin Lee Miller– Rune Linding– Nikolaj Blom– Søren Brunak

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