TPS

TPS reconstructs signaling pathways by integrating time-resolved phosphoproteomic data with protein-protein interaction networks using constraint-solving techniques from formal verification to enforce temporal coherence.

Key Features:

• Constraint-Solving Techniques: Employs constraint-solving methods adapted from formal verification to restrict pathway structures to biologically plausible configurations.
• Temporal Data Analysis: Analyzes time-resolved phosphoproteomic data to identify dynamic changes in phosphorylation states without requiring individual protein perturbations.
• Pathway Member Discovery: Identifies signaling pathway members that may not show differential phosphorylation, extending discovery beyond directly observable phosphosite changes.
• High-Throughput Phosphosite Modeling: Models over one hundred thousand dynamic phosphosites to provide large-scale coverage of cellular signaling dynamics.

Scientific Applications:

• Pathway Reconstruction: Reconstructs extensive signaling networks by integrating time series phosphoproteomic data with protein-protein interaction networks.
• Validation of Predictions: Supports validation using independent kinase mutant studies, exemplified by accurate substrate predictions in yeast osmotic stress responses.
• Discovery of Novel Pathways: Proposes new signaling connections in contexts such as human epidermal growth factor response and yeast osmotic stress, alongside recovery of known pathways.

Methodology:

Integrates time-resolved phosphoproteomic data with protein-protein interaction networks, applies constraint-solving techniques from formal verification, analyzes temporal phosphorylation changes, and systematically eliminates candidate pathway structures where a protein's activation or inactivation precedes its upstream regulators, enabling modeling of over one hundred thousand dynamic phosphosites.