WebGIVI

WebGIVI visualizes gene:iTerm associations extracted from biomedical literature to aid interpretation of large gene sets from high-throughput transcriptome studies.

Key Features:

• eGIFT integration: Extracts iTerms from biomedical literature using the eGIFT text-mining system and links them to genes.
• Data input: Accepts gene lists to retrieve gene symbols and corresponding iTerm lists and accepts two-column tab-separated data for visualization.
• Visualization methods: Provides Concept Map and Cytoscape Network Map representations of gene:iTerm pairs.
• Interactive network operations: Generates interactive network graphs that support filtering, sorting, and grouping of nodes.
• Scalability and output: Visualizes hundreds of nodes and produces high-resolution images suitable for publication.

Scientific Applications:

• Transcriptome interpretation: Maps gene lists to literature-derived iTerms to facilitate interpretation of high-throughput transcriptome data.
• Biological process and pathway exploration: Links genes with iTerms to reveal associated biological processes and pathways.
• Hypothesis generation: Identifies candidate biological concepts for downstream hypothesis development and experimental design.
• Figure generation: Produces publication-quality visualizations of gene:iTerm networks for dissemination and reporting.

Methodology:

iTerms are extracted from biomedical literature using the eGIFT text-mining system; visualizations are implemented using the Cytoscape framework and Data Driven Document (D3.js) JavaScript libraries.