PHONEMeS

PHONEMeS models signaling networks from untargeted phosphoproteomics mass spectrometry data by integrating kinase/phosphatase–substrate interactions to infer the flow of signal perturbations.


Key Features:

  • Input data: Uses high-content shotgun untargeted phosphoproteomic mass spectrometry data as primary input.
  • Interaction integration: Integrates kinase and phosphatase substrate–interaction information to connect phosphosites to upstream regulators.
  • Network modeling: Constructs logical network models that represent propagation of signaling perturbations.
  • Optimization formulation: Reformulated as an Integer Linear Program (ILP) to perform network inference.
  • Pathway scope: Can model deregulated pathways both upstream and downstream of specified deregulated kinases, not limited to direct perturbation targets.
  • Temporal analysis: Supports analysis of datasets with multiple time points to capture temporal propagation of signals.
  • Biomedical applicability: Has been applied to diverse datasets of medical relevance to investigate phosphosignaling mechanisms and drug modes of action.

Scientific Applications:

  • Signaling network reconstruction: Infer signaling network topology and directionality from phosphoproteomic perturbation data.
  • Kinase/phosphatase activity inference: Link observed phosphosite changes to candidate upstream kinases and phosphatases.
  • Pathway deregulation analysis: Explore upstream and downstream effects of deregulated kinases within signaling pathways.
  • Temporal signaling studies: Analyze time-course phosphoproteomic data to map temporal propagation of signaling events.
  • Drug mode-of-action investigation: Elucidate mechanisms of action of perturbations or therapeutics through inferred phosphosignaling networks.

Methodology:

PHONEMeS integrates kinase/phosphatase–substrate interaction data with shotgun untargeted phosphoproteomic measurements to construct logical network models and solves the resulting inference problem using an Integer Linear Program (ILP); it can incorporate multiple time points and model upstream/downstream deregulated kinase effects.

Topics

Details

Cost:
Free of charge
Tool Type:
library
Programming Languages:
R
Added:
5/28/2021
Last Updated:
11/24/2024

Operations

Publications

Gjerga E, Dugourd A, Tobalina L, Sousa A, Saez-Rodriguez J. PHONEMeS: Efficient Modeling of Signaling Networks Derived from Large-Scale Mass Spectrometry Data. Journal of Proteome Research. 2021;20(4):2138-2144. doi:10.1021/acs.jproteome.0c00958. PMID:33682416.

PMID: 33682416
Funding: - H2020 Health: 668858