ArticleFrontiers in physiology2016
MetaboTools: A Comprehensive Toolbox for Analysis of Genome-Scale Metabolic Models.
Article in Frontiers in physiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Endothelial SLC25A13 links glutamine metabolism to angiogenesis.EMBO molecular medicine · 2026Article
- NAViFluX: a visualization‑centric platform for interactive analysis, refinement and design of genome‑scale metabolic networks.Bioinformatics (Oxford, England) · 2026Article
- Review
- Merging metabolic modeling and imaging for screening therapeutic targets in colorectal cancer.NPJ systems biology and applications · 2025Article
- In silico metabolic modelling links microbiome-derived metabolites to risk factors of Alzheimer's disease.Gut microbes reports · 2025Article
- Extreme thermal environments: reservoirs of industrially important thermozymes.Frontiers in microbiology · 2025Review
- Merging Metabolic Modeling and Imaging for Screening Therapeutic Targets in Colorectal Cancer.bioRxiv : the preprint server for biology · 2024Article
- Transcriptome-based biomarker prediction for Parkinson's disease using genome-scale metabolic modeling.Scientific reports · 2024Article
- Article
- Development and applications of metabolic models in plant multi-omics research.Frontiers in plant science · 2024Review
- Mathematical reconstruction of the metabolic network in an in-vitro multiple myeloma model.PLoS computational biology · 2023Article
- Systems biology elucidates the distinctive metabolic niche filled by the human gut microbe Eggerthella lenta.PLoS biology · 2023Article
- Vibrio natriegens genome-scale modeling reveals insights into halophilic adaptations and resource allocation.Molecular systems biology · 2023Article
- Novel context-specific genome-scale modelling explores the potential of triacylglycerol production by Chlamydomonas reinhardtii.Microbial cell factories · 2023Article
- Machine Learning and Hybrid Methods for Metabolic Pathway Modeling.Methods in molecular biology (Clifton, N.J.) · 2023Review
- A Practical Guide to Integrating Multimodal Machine Learning and Metabolic Modeling.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Exploring synergies between plant metabolic modelling and machine learning.Computational and structural biotechnology journal · 2022Review
- Protocol for hybrid flux balance, statistical, and machine learning analysis of multi-omic data from the cyanobacteriumSTAR protocols · 2021Article
- Path to improving the life cycle and quality of genome-scale models of metabolism.Cell systems · 2021Review
- Metabolic modelling reveals broad changes in gut microbial metabolism in inflammatory bowel disease patients with dysbiosis.NPJ systems biology and applications · 2021Article
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3 authors.
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Abstract
Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Previous work, by us and others, revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. With the MetaboTools, we make our methods available to the broader scientific community. The MetaboTools consist of a protocol, a toolbox, and tutorials of two use cases. The protocol describes, in a step-wise manner, the workflow of data integration, and computational analysis. The MetaboTools comprise the Matlab code required to complete the workflow described in the protocol. Tutorials explain the computational steps for integration of two different data sets and demonstrate a comprehensive set of methods for the computational analysis of metabolic models and stratification thereof into different phenotypes. The presented workflow supports integrative analysis of multiple omics data sets. Importantly, all analysis tools can be applied to metabolic models without performing the entire workflow. Taken together, the MetaboTools constitute a comprehensive guide to the intra-model analysis of extracellular metabolomic data from microbial, plant, or human cells. This computational modeling resource offers a broad set of computational analysis tools for a wide biomedical and non-biomedical research community.
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