KinSwingR

KinSwingR integrates phosphosite data derived from mass-spectrometry data and kinase-substrate predictions to predict kinase activity.

Key Features:

• PWM Model Building: Functions build position weight matrix (PWM) models of kinase-substrates.
• Statistical Inference of Matches: Functions statistically infer PWM:substrate matches.
• Data Integration: Functions integrate phosphosite data and kinase-substrate predictions to infer kinase activity.

Scientific Applications:

• Kinase Activity Prediction: Predicts kinase activity from mass-spectrometry-derived phosphosite data and kinase-substrate predictions.
• Network-based Phosphoproteomics Analysis: Enables network-based kinase activity prediction by combining phosphoproteomics data with kinase-substrate relationship models.

Methodology:

KinSwingR builds PWM models of kinase-substrates, statistically infers PWM:substrate matches, and integrates these with phosphosite data to infer kinase activity.