Phosphoproteomic analysis of EGF stimulated MCF7 cells. This dataset is the basis for the development of modeling of signaling networks. A fundamental challenge in biology is to delineate the signaling pathways that govern cellular responses to genetic and environmental cues. Phosphoproteomics is an emerging technology that provides key data on activity levels of proteins under conditions of interest. However, the interpretation of these data is hampered by the lack of methods that can translate site-specific information into global maps of active proteins and signaling networks. To meet this challenge, we propose PHOTON, a method for integrating phosphorylation data with protein-protein interaction networks to identify active proteins and pathways and pinpoint functional phosphosites. We demonstrate the utility of PHOTON by applying it to interpret existing and novel phosphoproteomic datasets related to EGF and insulin responses. PHOTON substantially outperforms the widely-used cutoff approach, providing highly reproducible predictions that are more in line with current biological knowledge