title: Computational modeling of the EGF-receptor system: a paradigm for systems biology.
abstract: Computational models have rarely been used as tools by biologists but, when models provide experimentally testable predictions, they can be extremely useful. The epidermal growth factor receptor (EGFR) is probably the best-understood receptor system, and computational models have played a significant part in its elucidation. For many years, models have been used to analyze EGFR dynamics and to interpret mutational studies, and are now being used to understand processes including signal transduction, autocrine loops and developmental patterning. The success of EGFR modeling can be a guide to combining models and experiments productively to understand complex biological processes as integrated systems.
authors.affiliation: Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA. steven.wiley@pnl.gov
authors.forename: H Steven
authors.initials: HS
authors.lastname: Wiley
authors.forename: Stanislav Y
authors.initials: SY
authors.lastname: Shvartsman
authors.forename: Douglas A
authors.initials: DA
authors.lastname: Lauffenburger
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods* / Q000639:trends; D066246:ErbB Receptors / Q000737:chemistry / Q000378:metabolism*; D006801:Humans; D008954:Models, Biological; D011485:Protein Binding / Q000502:physiology; D015398:Signal Transduction / Q000502:physiology
chemical_list: D066246:ErbB Receptors