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@ARTICLE{Qi:8400,
      author       = {Qi, Y. and Dhiman, H.K. and Bhola, N.E. and Budyak, I. and
                      Kar, S. and Man, D. and Dutta, A. and Tirupula, K. and Carr,
                      B. and Grandis, J.R. and Bar-Joseph, Z. and
                      Klein-Seetharaman, J.},
      title        = {{S}ystematic prediction of human membrane receptor
                      interactions},
      journal      = {Proteomics},
      volume       = {9},
      issn         = {1615-9853},
      address      = {Weinheim},
      publisher    = {Wiley VCH},
      reportid     = {PreJuSER-8400},
      pages        = {5243 - 5255},
      year         = {2009},
      note         = {This work was supported in part by National Science
                      Foundation Grants ITR 0225656, CAREER 0448453 and CAREER
                      CC044917, National Institutes of Health Grants NLM108730,
                      R01 CA098372 and AI060422 and the Sofya Kovalvskaya Award
                      (to J. K. S.) from the Humboldt Foundation.},
      abstract     = {Membrane receptor-activated signal transduction pathways
                      are integral to cellular functions and disease mechanisms in
                      humans. Identification of the full set of proteins
                      interacting with membrane receptors by high-throughput
                      experimental means is difficult because methods to directly
                      identify protein interactions are largely not applicable to
                      membrane proteins. Unlike prior approaches that attempted to
                      predict the global human interactome, we used a
                      computational strategy that only focused on discovering the
                      interacting partners of human membrane receptors leading to
                      improved results for these proteins. We predict specific
                      interactions based on statistical integration of biological
                      data containing highly informative direct and indirect
                      evidences together with feedback from experts. The predicted
                      membrane receptor interactome provides a system-wide view,
                      and generates new biological hypotheses regarding
                      interactions between membrane receptors and other proteins.
                      We have experimentally validated a number of these
                      interactions. The results suggest that a framework of
                      systematically integrating computational predictions, global
                      analyses, biological experimentation and expert feedback is
                      a feasible strategy to study the human membrane receptor
                      interactome.},
      keywords     = {Computational Biology: methods / Humans / Protein
                      Interaction Mapping: methods / Proteome: analysis /
                      Proteome: metabolism / Proteomics: methods / Receptor,
                      Epidermal Growth Factor: analysis / Receptor, Epidermal
                      Growth Factor: metabolism / Receptors, Cell Surface:
                      analysis / Receptors, Cell Surface: metabolism / Signal
                      Transduction / Systems Biology: methods / Proteome (NLM
                      Chemicals) / Receptors, Cell Surface (NLM Chemicals) / EGFR
                      protein, human (NLM Chemicals) / Receptor, Epidermal Growth
                      Factor (NLM Chemicals) / J (WoSType)},
      cin          = {ISB-2},
      ddc          = {540},
      cid          = {I:(DE-Juel1)ISB-2-20090406},
      pnm          = {Programm Biosoft},
      pid          = {G:(DE-Juel1)FUEK443},
      shelfmark    = {Biochemical Research Methods / Biochemistry $\&$ Molecular
                      Biology},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:19798668},
      pmc          = {pmc:PMC3076061},
      UT           = {WOS:000273393900006},
      doi          = {10.1002/pmic.200900259},
      url          = {https://juser.fz-juelich.de/record/8400},
}