Elucidation of Signaling Pathways from Large-Scale Phosphoproteomic Data Using Protein Interaction Networks

Jan Daniel Rudolph, Marjo de Graauw, Bob van de Water, Tamar Geiger*, Roded Sharan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Phosphoproteomic experiments typically identify sites within a protein that are differentially phosphorylated between two or more cell states. 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, especially as the phosphoproteome is often undersampled. Here, we describe PHOTON, a method for interpreting phosphorylation data within their signaling context, as captured by protein-protein interaction networks, to identify active proteins and pathways and pinpoint functional phosphosites. We apply PHOTON to interpret existing and novel phosphoproteomic datasets related to epidermal growth factor and insulin responses. PHOTON substantially outperforms the widely used cutoff approach, providing highly reproducible predictions that are more in line with current biological knowledge. Altogether, PHOTON overcomes the fundamental challenge of delineating signaling pathways from large-scale phosphoproteomic data, thereby enabling translation of environmental cues to downstream cellular responses.

Original languageEnglish
Pages (from-to)585-593.e3
JournalCell Systems
Issue number6
StatePublished - 21 Dec 2016


FundersFunder number
Edmond J. Safra Center for Bioinformatics
I-CORE Centers of Excellence in Gene Regulation in Complex Human Disease41/11
Israel Science Foundation241/11
Tel Aviv University
Israeli Centers for Research Excellence757/12


    • mass spectrometry
    • phosphorylation
    • protein interaction networks
    • proteomics
    • signal transduction


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