BioEMMA: Automated Generation of Model-Specific Escher-Compatible Maps from KEGG Pathways.

Vladislav A Kachnov, Maryam A Esembaeva, Ekaterina V Melikhova, Mikhail A Kulyashov

Abstract read

In one paragraph

Article in Biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Vladislav A KachnovDepartment of Computational Biology, Scientific Center of Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sirius, Russia.ORCID 0009-0005-5018-755X

Maryam A EsembaevaDepartment of Computational Biology, Scientific Center of Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sirius, Russia.ORCID 0000-0003-2591-459X

Ekaterina V MelikhovaDepartment of Computational Biology, Scientific Center of Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sirius, Russia.

Mikhail A KulyashovDepartment of Computational Biology, Scientific Center of Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sirius, Russia.ORCID 0000-0002-4808-0922

Funding

Russian Science Foundation №25-24-20098

6 · The paper itself

Abstract

Genome-scale metabolic models are widely used to investigate cellular metabolism, but their interpretation and comparison are limited by the lack of reproducible pathway-level visualizations with a common spatial organization. This study presents BioEMMA, a Python-based tool for the automated generation of model-specific metabolic pathway maps in the Escher JSON format using coordinate information from curated KEGG pathway maps. BioEMMA parses KGML files, map reaction and metabolite identifiers to model database namespaces, filters pathway elements according to an input SBML model, adds non-primary metabolites, reconstructs Escher-compatible layouts, and supports flux visualization. The tool was integrated into a reproducible BioUML workflow for metabolic model reconstruction. BioEMMA was evaluated using the e_coli_core model and the KEGG glycolysis/gluconeogenesis pathway while generating a model-specific map with overlaid FBA fluxes. It was then applied to compare

Indexed as

Escher mapsflux balance analysisgenome-scale metabolic modelsKEGG pathwaysmetabolic model reconstructionmetabolic pathway visualizationmodel comparison

Identifiers

PMID42737924

DOI10.3390/biology15171493

PMCPMC13564630

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.