ArticlePLoS computational biology2020
Medusa: Software to build and analyze ensembles of genome-scale metabolic network reconstructions.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- XomicsToModel: omics data integration and generation of thermodynamically consistent metabolic models.Nature protocols · 2026Article
- Article
- Shu: visualization of high-dimensional biological pathways.Bioinformatics (Oxford, England) · 2024Article
- Flux sampling in genome-scale metabolic modeling of microbial communities.BMC bioinformatics · 2024Article
- Genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer.iScience · 2023Article
- Flux Sampling in Genome-scale Metabolic Modeling of Microbial Communities.bioRxiv : the preprint server for biology · 2023Article
- Ensemble-based genome-scale modeling predicts metabolic differences between macrophage subtypes in colorectal cancer.bioRxiv : the preprint server for biology · 2023Article
- Enzyme-constrained models predict the dynamics of Saccharomyces cerevisiae growth in continuous, batch and fed-batch bioreactors.Microbial biotechnology · 2022Article
- Constraint-Based Reconstruction and Analyses of Metabolic Models: Open-Source Python Tools and Applications to Cancer.Frontiers in oncology · 2022Review
- Elucidating Plant-Microbe-Environment Interactions Through Omics-Enabled Metabolic Modelling Using Synthetic Communities.Frontiers in plant science · 2022Article
- Novel Drivers of Virulence in Clostridioides difficile Identified via Context-Specific Metabolic Network Analysis.mSystems · 2021Article
- Addressing uncertainty in genome-scale metabolic model reconstruction and analysis.Genome biology · 2021Review
- Systematically gap-filling the genome-scale metabolic model of CHO cells.Biotechnology letters · 2021Article
- Human physiomimetic model integrating microphysiological systems of the gut, liver, and brain for studies of neurodegenerative diseases.Science advances · 2021Article
- Guiding the Refinement of Biochemical Knowledgebases with Ensembles of Metabolic Networks and Machine Learning.Cell systems · 2020Article
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Authors and funding
3 authors.
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Abstract
Uncertainty in the structure and parameters of networks is ubiquitous across computational biology. In constraint-based reconstruction and analysis of metabolic networks, this uncertainty is present both during the reconstruction of networks and in simulations performed with them. Here, we present Medusa, a Python package for the generation and analysis of ensembles of genome-scale metabolic network reconstructions. Medusa builds on the COBRApy package for constraint-based reconstruction and analysis by compressing a set of models into a compact ensemble object, providing functions for the generation of ensembles using experimental data, and extending constraint-based analyses to ensemble scale. We demonstrate how Medusa can be used to generate ensembles and perform ensemble simulations, and how machine learning can be used in conjunction with Medusa to guide the curation of genome-scale metabolic network reconstructions. Medusa is available under the permissive MIT license from the Python Packaging Index (https://pypi.org) and from github (https://github.com/opencobra/Medusa), and comprehensive documentation is available at https://medusa.readthedocs.io/en/latest.
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