DynaPho

DynaPho analyzes time-course phosphoproteomics data to characterize temporal changes in biological pathways, kinase activities, interaction networks, and kinase-substrate relationships.

Key Features:

• Biological Pathway Transition Analysis: Tracks and visualizes changes in biological pathways over time to provide a dynamic view of cellular signaling processes from phosphoproteomics data.
• Kinase Activity Profiling: Assesses kinase activity across time points to elucidate the roles of kinases in regulating phosphorylation events.
• Interaction Network Dynamics: Explores temporal evolution of protein interaction networks and phosphorylation-dependent network changes.
• Predicted Kinase-Substrate Associations: Predicts potential kinase-substrate relationships to aid identification of novel regulatory mechanisms within signaling pathways.

Scientific Applications:

• Temporal signaling analysis: Characterizing time-dependent pathway activity and signaling dynamics from longitudinal phosphoproteomics experiments.
• Kinase regulation discovery: Identifying kinases with changing activity profiles that may drive dynamic phosphorylation events.
• Network dynamics characterization: Mapping temporal rewiring of protein interaction networks associated with phosphorylation changes.
• Kinase-substrate hypothesis generation: Proposing candidate kinase-substrate pairs for experimental validation.
• Phosphoproteomics data interpretation: Converting large-scale time-course phosphorylation datasets into testable biological hypotheses.

Methodology:

Computational analysis is organized into analytic modules implementing biological pathway transition analysis, kinase activity profiling, interaction network dynamics, and prediction of kinase-substrate associations on time-course phosphoproteomics datasets.