title: An integrated Bayesian framework for identifying phosphorylation networks in stimulated cells.
abstract: One of the primary mechanisms of signal transduction in cells is protein phosphorylation. Upon ligand stimulation a series of phosphorylation events take place which eventually lead to transcription. Different sets of phosphorylation events take place due to different stimulating ligands in different types of cells. Knowledge of these phosphorylation events is essential to understand the underlying signaling mechanisms. We have developed a Bayesian framework to infer phosphorylation networks from time series measurements of phosphosite concentrations upon ligand stimulation. To increase the prediction accuracy we integrated different types of data, e.g., amino acid sequence data, genomic context data (gene fusion, gene neighborhood, and phylogentic profiles), primary experimental evidence (physical protein interactions and gene coexpression), manually curated pathway databases, and automatic literature mining with time series data in our inference framework. We compared our results with data available from public databases and report a high level of prediction accuracy.
authors.affiliation: Systems Biology Ireland, Conway Institute, University College Dublin (UCD), Belfield, Dublin 4, Ireland. tapesh.santra@ucd.ie
authors.forename: Tapesh
authors.initials: T
authors.lastname: Santra
authors.forename: Boris
authors.initials: B
authors.lastname: Kholodenko
authors.forename: Walter
authors.initials: W
authors.lastname: Kolch
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D016208:Databases, Factual; D004815:Epidermal Growth Factor / Q000494:pharmacology; D066246:ErbB Receptors / Q000378:metabolism; D020869:Gene Expression Profiling; D006367:HeLa Cells; D006801:Humans; D008954:Models, Biological; D010766:Phosphorylation / Q000187:drug effects; D011494:Protein Kinases / Q000378:metabolism; D011506:Proteins / Q000235:genetics / Q000378:metabolism; D015203:Reproducibility of Results; D015398:Signal Transduction / Q000187:drug effects / Q000235:genetics / Q000502:physiology*; D049490:Systems Biology / Q000379:methods; D018511:Systems Integration
chemical_list: D011506:Proteins; D004815:Epidermal Growth Factor; D011494:Protein Kinases; D066246:ErbB Receptors