hipathia

hipathia computes signal transduction activity in cellular signaling pathways from transcriptomic data to quantify changes in signaling-circuit activity driven by gene expression values and mutations.

Key Features:

• Iterative Algorithm: Employs an iterative algorithm that calculates signal intensity at network nodes by combining gene expression levels and incoming signal intensities to each node.
• Functional Analysis: Computes the signal arriving at functions annotated to each pathway to assess how pathway perturbations affect cellular functionalities.
• High-Throughput Estimations: Provides high-throughput estimations of cell functionalities influenced by gene activity across cohort-level and personalized (patient-level) analyses.
• Validation: Accuracy validated using data from 5,640 patients across 12 cancer types.

Scientific Applications:

• Precision Medicine: Models cell signaling using biological knowledge to interpret cellular mechanisms underlying disease and drug actions relevant to precision medicine.
• Disease Diagnosis and Prognosis: Measures circuit activity that can be correlated with clinical outcomes such as patient survival to support diagnostic and prognostic assessments.
• Therapeutic Interventions Assessment: Assesses therapeutic interventions by observing changes in pathway and circuit activities, enabling evaluation of targeted therapies.

Methodology:

Recodes gene expression values and/or mutations into measurements of signaling-circuit activity; models signal transduction using biological knowledge to simulate signal propagation through pathways; quantifies circuit activity changes from gene expression and mutation data; supports analyses at cohort and individual (patient) levels.