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

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Novel approaches to study kinase and GTPase signaling, Plate-forme Génomique fonctionnelle Bordeaux Aquitaine, Bordeaux, France, September 26-28, 2007

Novel approaches to study kinase and GTPase signaling, Plate-forme Génomique fonctionnelle Bordeaux Aquitaine, Bordeaux, France, September 26-28, 2007

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

  • Systematic discovery of phosphorylation networks Combining linear motifs and protein interactions Lars Juhl Jensen EMBL Heidelberg
  • Lars Juhl Jensen
  •  
  •  
  • promoter analysis
  •  
  • genome visualization
  •  
  • protein function prediction
  •  
  •  
  •  
  • data integration
  •  
  • dynamic interactions
  •  
  • prediction of interactions
  • http://string.embl.de
  • prediction of interactions
  • http://networkin.info
  • the starting point
  • phosphoproteomics
  • mass spectrometry
  •  
  • phosphorylation sites
  • in vivo
  • kinases are unknown
  • HTP kinase assays
  • in vitro
  • no context
  • what a kinase could do
  • not what it actually does
  • computational methods
  • sequence motifs
  •  
  • kinase families
  • phosphorylation sites
  • overprediction
  • no context
  • what a kinase could do
  • not what it actually does
  • in vitro
  • in vivo
  • context
  • localization
  • expression
  • co-activators
  • scaffolders
  • protein networks
  •  
  • the idea
  • mass spectrometry
  •  
  • phosphorylation sites
  • sequence motifs
  •  
  • kinase families
  • protein networks
  •  
  • context
  • in vitro
  • in vivo
  • “ shake and bake”
  •  
  • NetworKIN
  • the context network
  • STRING
  • functional interactions
  • 373 genomes
  •  
  • genomic context methods
  • gene neighborhood
  •  
  • gene fusion
  •  
  • phylogenetic profiles
  •  
  • primary experimental data
  • protein interactions
  •  
  • genetic interactions
  •  
  • gene coexpression
  •  
  • literature mining
  •  
  • curated knowledge
  •  
  • many sources
  • different formats
  • different gene identifiers
  • redundancy
  • variable quality
  • spread over many species
  • benchmarking
  •  
  • transfer by orthology
  •  
  • combine all evidence
  •  
  • the results
  •  
  • 7797 predictions
  • 1790 substrates
  • 69 kinases
  •  
  • benchmarking
  • Phospho.ELM
  •  
  • 2.5-fold better accuracy
  • context is crucial
  • localization
  •  
  • visualization
  •  
  • ATM signaling
  •  
  • small-scale validation
  • ATM phosphorylates Rad50
  •  
  • Cdk1 phosphorylates 53BP1
  •  
  • high-throughput validation
  • multiple reaction monitoring
  •  
  • the future
  • NetPhorest
  • sequence motifs
  • in vivo
  • in vitro
  • automatic pipeline
  • data organization
  •  
  • benchmarking
  • selection
  •  
  • ~200 kinases
  • ~100 SH2 domains
  • ~15 PTB domains
  • upstream signaling
  • downstream signaling
  • ordered signaling events
  • signaling pathways
  • 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