TriPOINT

TriPOINT integrates non-coding regulatory elements into graph-based pathway analysis to prioritize gene significance within biological pathways.

Key Features:

• Graph-Based Pathway Representation: Uses graph representations to model pathways and examine upstream and downstream gene interactions.
• Integration of Non-Coding Factors: Systematically incorporates non-coding regulatory regions when evaluating gene regulation and significance.
• Gene Significance Prioritization: Combines coding and non-coding information to identify and prioritize genes significant under specific conditions such as disease phenotypes.
• Triangulation of Perturbation Origins: Employs a triangulation approach to infer perturbation origins affecting pathway components.
• Java Implementation: Implemented in Java for computational execution of analyses.

Scientific Applications:

• Disease Phenotype Analysis: Identifies regulatory elements and genes implicated in disease phenotypes by integrating coding and non-coding data.
• Pathway Enrichment Studies: Enables pathway enrichment analyses that consider non-coding regulatory influences on pathway activity.
• Gene Interaction Networks: Supports analysis of gene interaction networks within pathways to study systems-level regulatory effects.

Methodology:

Uses graph-based pathway modeling, systematic integration of coding and non-coding region data, and a triangulation approach to infer perturbation origins.