Computer ScienceBiologyMedicine

C. E. Buss, Ao Li, E. H. Gilglioni, Mayank Bansal, Sumeet Pal Singh, Latifa Bakiri, Alessandra K Cardozo, Esteban N. Gurzov

2026.6.23FEBS Open Bio

DOI: 10.1002/2211-5463.70288

Abstract

While simplistic volcano plot visualizations of multi-omics changes can highlight the most critical genomic, transcriptomic, or proteomic features, integrative frameworks combining literature evidence, pathway associations, and functional annotation remain limited. We present MagmaFlow, a cross-platform application offering three key capabilities: literature-based gene scoring, interactive pathway-to-volcano mapping, and synchronized cross-view updates. The literature module retrieves gene associations from PubMed via PubTator3, provides direct PubMed identifier (PMID) links, and ranks genes by context-specific relevance. The pathway module visualizes enrichment as multi-layer circle plots displaying cross-pathway membership, automatically synchronized with volcano selections. Interactive features include smart label positioning, drag-and-drop annotation, double-click gene targeting, and customizable styles for publication-quality figures. Thus, MagmaFlow transforms volcano plot analysis from static display into dynamic biological interpretation. To our knowledge, this is the first tool integrating artificial intelligence-powered literature contextualization and enrichment analysis to convert differential expression data into actionable insights.

Citation format

BUSS, C. E., et al. Magmaflow: A desktop platform for artificial intelligence-driven expression analysis. FEBS Open Bio, 2026.