Exploration and comparative visualization of metabolic networks in GEMs with MMINT
Genome-scale metabolic models (GEMs) are essential tools in systems and engineering biology, enabling the simulation of genome-encoded pathways, predicting metabolic fluxes and emergent phenotypes. GEM network visualization tools can facilitate the interpretation of the predictions derived from GEMs. Here, we present metabolic modeling interactive network tool (MMINT), a tool specifically designed for the exploration and comparison of GEM flux distribution networks. MMINT enables interactive toggling of source and target metabolites and reactions and highlights similarities and differences between sets of predicted fluxes. We demonstrate MMINT's capabilities using the <i>Pyrococcus furiosus</i> GEM iPfu, showcasing its application in distinguishing the metabolic drivers of acetate- and ethanol-producing phenotypes. By providing an intuitive and responsive model exploration experience, MMINT addresses the need for a tool that simplifies the interpretation of GEM outputs and supports the identification of metabolic drivers of phenotypes.
Authors
- Philip Kilby (ORCID: https://orcid.org/0000-0001-7349-1179)
- Andrew C. Warden (ORCID: https://orcid.org/0000-0003-2683-9798)
- Amy M. Paten (ORCID: https://orcid.org/0000-0003-0420-2155)
- Juan Pablo Molina Ortiz (ORCID: https://orcid.org/0000-0003-4432-6689)
- Matthew J. Morgan
Institutions
- Commonwealth Scientific and Industrial Research Organisation (AU)
- Data61 (AU)
Publication Details
- Journal
- iScience
- Published
- 2025-10-21
- DOI
- https://doi.org/10.1016/j.isci.2025.113797
- Primary Topic
- Microbial Metabolic Engineering and Bioproduction
- Type
- article
- Field-Weighted Citation Impact
- 0.00