combining sequence motifs and protein interactions to unravel complex phosphorylation networks

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Analysis of complex biological systems, Shanghai Jiao Tong University, Shanghai, China, August 19, 2009.

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Combining sequence motifs and protein interactions to unravel complex phosphorylation networks

Lars Juhl Jensen

the problem

phosphoproteomics

Linding, Jensen, Ostheimer et al., Cell, 2007

in vivo phosphosites

kinases are unknown

functions are unknown

sequence specificity

peptide assays

Miller, Jensen et al., Science Signaling, 2008

domain-specific

in vitro

no context

what could happen

not what does happen

machine-learning methods

sequence motifs

Miller, Jensen et al., Science Signaling, 2008

domain-specific

group-specific

no context

what could happen

not what does happen

in vitro

in vivo

context

co-activators

protein scaffolds

subcellular localization

spatial expression

temporal expression

association networks

Linding, Jensen, Ostheimer et al., Cell, 2007

the idea

Linding, Jensen, Ostheimer et al., Cell, 2007

the sequence motifs

NetPhorest

automated pipeline

Miller, Jensen et al., Science Signaling, 2008

data organization

Miller, Jensen et al., Science Signaling, 2008

compilation of datasets

redundancy reduction

training and evaluation

classifier selection

motif atlas

179 kinases

89 SH2 domains

8 PTB domains

BRCT domains

WW domains

14-3-3 proteins

use cases

Miller, Jensen et al., Science Signaling, 2008

the context network

NetworKIN

Linding, Jensen, Ostheimer et al., Cell, 2007

STRING

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

protein interactions

Jensen & Bork, Science, 2008

gene coexpression

localization

Linding, Jensen, Ostheimer et al., Cell, 2007

benchmarking

Phospho.ELM

Linding, Jensen, Ostheimer et al., Cell, 2007

2.5-fold better accuracy

the experiments

ATM signaling

Linding, Jensen, Ostheimer et al., Cell, 2007

Linding, Jensen, Ostheimer et al., Cell, 2007

small-scale validation

ATM phosphorylates Rad50

Linding, Jensen, Ostheimer et al., Cell, 2007

high-throughput validation

multiple reaction monitoring

Linding, Jensen, Ostheimer et al., Cell, 2007

the future

new scoring scheme

two separate scores

one combined score

path length penalty

model organisms

S. cerevisiae

D. melanogaster

C. elegans

(S. pombe)

other modifications

phosphatases

ubiquitylation

F-box proteins

acetylation

AcknowledgmentsNetPhorest.info

– Rune Linding– Martin Lee Miller– Francesca Diella– Claus Jørgensen– Michele Tinti– Lei Li– Marilyn Hsiung– Sirlester A. Parker– Jennifer Bordeaux– Thomas Sicheritz-Pontén– Marina Olhovsky– Adrian Pasculescu– Jes Alexander– Stefan Knapp– Nikolaj Blom– Peer Bork– Shawn Li– Gianni Cesareni– Tony Pawson– Benjamin E. Turk– Michael B. Yaffe– Søren Brunak

STRING.embl.de– Christian von Mering– Michael Kuhn– Manuel Stark– Samuel Chaffron– Chris Creevey– Jean Muller– Tobias Doerks– Philippe Julien– Alexander Roth– Milan Simonovic– Jan Korbel– Berend Snel– Martijn Huynen– Peer Bork

NetworKIN.info– Rune Linding– Gerard Ostheimer– Heiko Horn– Martin Lee Miller– 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

larsjuhljensen

Thank you

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