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NAViFluX: a visualization‑centric platform for interactive analysis, refinement and design of genome‑scale metabolic networks.

Manjunatha Beduru Krishnamurthy·Pasupula Sridhar Harish·Abhishek Subramanian
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Abstract

MOTIVATION: Genome-scale metabolic network (GSMN) models enable flux-based metabolite fate discovery, metabolic engineering, drug target identification, and multi-omics integration. However, programming requirements, architectural complexity, and limited visualization support impede its adoption by the broader scientific community. Existing tools exclusively specialize in GSMN analyses or visualization while lacking important features such as pathway-specific views, database-integrated refinement, and comprehensive enrichment and perturbation analyses. RESULTS: Here, we present NAViFluX (metabolic Network Analysis and Visualization of Flux), a visualization-centric, web browser-based tool that unifies native pathway/subsystem map generation, interactive model refinement via KEGG/BiGG, pathway merging and modules for flux computations, topology, and functional enrichment all within network views. Using three independent case studies on Escherichia coli, the utility of NAViFluX for characterization of nutrient-specific metabolic adaptations, enhancing gene essentiality predictions and interpretability, and rational design of an optimized carbon-fixing metabolic state is demonstrated. AVAILABILITY AND IMPLEMENTATION: All source code and supplementary files associated with the case studies are publicly available via Zenodo at https://zenodo.org/records/19107831. NAViFluX can be easily installed as a standalone software through https://github.com/bnsb-lab-iith/NAViFluX.

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Metabolic Networks and PathwaysSoftwareEscherichia coliGenomicsJournal ArticleResearch Support, Non-U.S. Gov't

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Manjunatha Beduru Krishnamurthy, Pasupula Sridhar Harish, Abhishek Subramanian. 2026-05-03. NAViFluX: a visualization‑centric platform for interactive analysis, refinement and design of genome‑scale metabolic networks.. https://doi.org/10.1093/bioinformatics%2Fbtag191

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