title: Collecting and organizing systematic sets of protein data.
abstract: Systems biology, particularly of mammalian cells, is data starved. However, technologies are now in place to obtain rich data, in a form suitable for model construction and validation, that describes the activities, states and locations of cell-signalling molecules. The key is to use several measurement technologies simultaneously and, recognizing each of their limits, to assemble a self-consistent compendium of systematic data.
authors.affiliation: Center for Cell Decision Processes, Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA.
authors.forename: John G
authors.initials: JG
authors.lastname: Albeck
authors.forename: Gavin
authors.initials: G
authors.lastname: MacBeath
authors.forename: Forest M
authors.initials: FM
authors.lastname: White
authors.forename: Peter K
authors.initials: PK
authors.lastname: Sorger
authors.forename: Douglas A
authors.initials: DA
authors.lastname: Lauffenburger
authors.forename: Suzanne
authors.initials: S
authors.lastname: Gaudet
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods* / Q000706:statistics & numerical data; D030562:Databases, Protein; D005786:Gene Expression Regulation; D006801:Humans; D007118:Immunoassay; D008954:Models, Biological; D011499:Protein Processing, Post-Translational