SELPHI

SELPHI analyzes phospho-proteomics datasets to identify correlations among phospho-sites, phospho-peptides, kinases, and phosphatases and to reveal condition-specific signaling network wiring.

Key Features:

• Correlation-Based Analysis: Employs correlation analysis to identify associations between phospho-sites, kinases/phosphatases, and phospho-peptides, supporting inference of signaling flow.
• Condition-Specific Network Discovery: Reveals condition- or cell-specific network wiring to detect relationships involving less-characterized kinases that may be masked by well-studied pathways.

Scientific Applications:

• Erlotinib-treated cancer cell phospho-proteomics: Applied to phospho-proteomics data from cancer cells treated with erlotinib (a tyrosine kinase inhibitor, TKI), SELPHI identified MET and EPHA2 kinases as contributors to erlotinib resistance in TKI-sensitive strains.

Methodology:

Uses a correlation analysis framework that systematically evaluates phospho-proteomics data to map kinase/phosphatase and phospho-peptide interactions.