ReactomeFIViz

ReactomeFIViz performs pathway- and network-based analysis of high-throughput biological data to identify gene signatures, perform pathway enrichment, and integrate multiple genomic data types within a gene functional interaction and Reactome-curated pathway context.

Key Features:

• Cytoscape integration: Implemented as a Cytoscape application for network-based analysis and visualization workflows.
• Gene functional interaction network: Leverages a gene functional interaction network integrated with human-curated pathways from Reactome and other pathway databases.
• Pathway and network contextualization: Projects complex biological data onto pathway and network contexts to reveal patterns obscured in raw datasets.
• Gene signature identification: Searches for gene signatures within gene expression datasets to identify genes associated with specific biological processes or conditions.
• Pathway enrichment analysis: Performs pathway enrichment analysis to identify pathways significantly associated with input gene lists.
• Integration of genomic data types: Integrates multiple genomic data types into pathway contexts using probabilistic graphical models.

Scientific Applications:

• High-throughput data analysis: Analysis of large-scale, noisy experimental datasets to extract pathway- and network-level signals.
• Functional interpretation of gene lists: Interpreting functional implications of gene lists via pathway enrichment and network context.
• Complex disease research: Knowledge discovery and mechanistic exploration in complex diseases, including cancer, through pathway- and network-based analyses.

Methodology:

Utilizes a gene functional interaction network integrated with human-curated Reactome and other pathway databases; employs probabilistic graphical models to integrate multiple genomic data types; performs pathway enrichment analysis and gene signature searches; implemented as a Cytoscape application.