Evidence map›Paper›PMID 39921902›Full record

ArticleBioinformatics (Oxford, England)2025

COBREXA 2: tidy and scalable construction of complex metabolic models.

Miroslav Kratochvíl, St Elmo Wilken, Oliver Ebenhöh, Reinhard Schneider, Venkata P Satagopam

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Miroslav KratochvílLuxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg.ORCID 0000-0001-7356-4075
St Elmo WilkenInstitute of Quantitative and Theoretical Biology, Heinrich Heine University, Düsseldorf, North Rhine-Westphalia 40225, Germany.ORCID 0000-0002-4113-2590
Oliver EbenhöhInstitute of Quantitative and Theoretical Biology, Heinrich Heine University, Düsseldorf, North Rhine-Westphalia 40225, Germany.ORCID 0000-0002-7229-7398
Reinhard SchneiderLuxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg.ORCID 0000-0002-8278-1618
Venkata P SatagopamLuxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg.ORCID 0000-0002-6532-5880

Funding

European Union's Horizon 2020 Programme
6 · The paper itself

Abstract

summaryConstraint-based metabolic models offer a scalable framework to investigate biological systems using optimality principles. Construction and simulation of detailed models that utilize multiple kinds of constraint systems pose a significant coding overhead, complicating implementation of new types of analyses. We present an improved version of the constraint-based metabolic modeling package COBREXA, which utilizes a hierarchical model construction framework that decouples the implemented analysis algorithms into independent, yet re-combinable, building blocks. By removing the need to re-implement modeling components, assembly of complex metabolic models is simplified, which we demonstrate on use-cases of resource-balanced models, and enzyme-constrained flux balance models of interacting bacterial communities. Notably, these models show improved predictive capabilities in both monoculture and community settings. In perspective, the re-usable model-building components in COBREXA 2 provide a sustainable way to handle increasingly complex models in constraint-based modeling. AVAILABILITY AND IMPLEMENTATION: COBREXA 2 is available from https://github.com/COBREXA/COBREXA.jl, and from Julia package repositories. COBREXA 2 works on all major operating systems and computer architectures. Documentation is available at https://cobrexa.github.io/COBREXA.jl/.

Indexed as

Computational BiologyMetabolic Networks and PathwaysModels, BiologicalSoftwareAlgorithmsComputer Simulation

Identifiers

PMID39921902
PMCPMC11842047

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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.