title: Experimental and computational tools useful for (re)construction of dynamic kinase-substrate networks.
abstract: The explosion of site- and context-specific in vivo phosphorylation events presents a potentially rich source of biological knowledge and calls for novel data analysis and modeling paradigms. Perhaps the most immediate challenge is delineating detected phosphorylation sites to their effector kinases. This is important for (re)constructing transient kinase-substrate interaction networks that are essential for mechanistic understanding of cellular behaviors and therapeutic intervention, but has largely eluded high-throughput protein-interaction studies due to their transient nature and strong dependencies on cellular context. Here, we surveyed some of the computational approaches developed to dissect phosphorylation data detected in systematic proteomic experiments and reviewed some experimental and computational approaches used to map phosphorylation sites to their effector kinases in efforts aimed at reconstructing biological signaling networks.
authors.affiliation: Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Canada.
authors.forename: Chris Soon Heng
authors.initials: CS
authors.lastname: Tan
authors.forename: Rune
authors.initials: R
authors.lastname: Linding
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D006801:Humans; D010770:Phosphotransferases / Q000032:analysis* / Q000378:metabolism; D025941:Protein Interaction Mapping / Q000379:methods*; D020543:Proteome / Q000032:analysis / Q000378:metabolism; D015398:Signal Transduction
chemical_list: D020543:Proteome; D010770:Phosphotransferases