Ligand binding to cell surface receptors initiates a cascade of signaling events regulated by dynamic phosphorylation events on a multitude of pathway proteins. Quantitative features, including intensity, timing, and duration of phosphorylation of particular residues, may play a role in determining cellular response, but experimental data required for analysis of these features have not previously been available. To understand the dynamic operation of signaling cascades, we have developed a method enabling the simultaneous quantification of tyrosine phosphorylation of specific residues on dozens of key proteins in a time-resolved manner, downstream of epidermal growth factor receptor (EGFR) activation. Tryptic peptides from four different EGFR stimulation time points were labeled with four isoforms of the iTRAQ reagent to enable downstream quantification. After mixing of the labeled samples, tyrosine-phosphorylated peptides were immunoprecipitated with an anti-phosphotyrosine antibody and further enriched by IMAC before LC/MS/MS analysis. Database searching and manual confirmation of peptide phosphorylation site assignments led to the identification of 78 tyrosine phosphorylation sites on 58 proteins from a single analysis. Replicate analyses of a separate biological sample provided both validation of this first data set and identification of 26 additional tyrosine phosphorylation sites and 18 additional proteins. iTRAQ fragment ion ratios provided time course phosphorylation profiles for each site. The data set of quantitative temporal phosphorylation profiles was further characterized by self-organizing maps, which resulted in identification of several cohorts of tyrosine residues exhibiting self-similar temporal phosphorylation profiles, operationally defining dynamic modules in the EGFR signaling network consistent with particular cellular processes. The presence of novel proteins and associated tyrosine phosphorylation sites within these modules indicates additional components of this network and potentially localizes the topological action of these proteins. Additional analysis and modeling of the data generated in this study are likely to yield more sophisticated models of receptor tyrosine kinase-initiated signal transduction, trafficking, and regulation.