ArticleMetabolic engineering2023
Guidelines for extracting biologically relevant context-specific metabolic models using gene expression data.
Article in Metabolic engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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21 citing papers in PubMed.
- Improving recombinant protein productivity in CHO cells via multi-omics data integration.Bioresources and bioprocessing · 2026Review
- Unraveling Aberrant Metabolic Patterns in Alzheimer's Disease Subtypes: From Perturbed Metabolic Pathways to Candidate Drug Targets.Molecular neurobiology · 2026Article
- A community reconstruction of Chinese hamster metabolism and structural systems biology elucidate metabolic rewiring in lactate-free CHO cells.Cell systems · 2026Article
- Patient-specific modeling identifies metabolic interventions for reversing glucose use reprogramming in alcohol-associated hepatitis.Communications biology · 2026Article
- XomicsToModel: omics data integration and generation of thermodynamically consistent metabolic models.Nature protocols · 2026Article
- Evaluating transcriptomic integration for cyanobacterial constraint-based metabolic modelling.Frontiers in bioinformatics · 2026Article
- RBApy: extending resource allocation modeling to eukaryotes in complex environments.Bioinformatics advances · 2026Article
- Modelling reliable metabolic phenotypes by analysing the context-specific transcriptomics data.NPJ systems biology and applications · 2025Article
- Metatranscriptomics-based metabolic modeling of patient-specific urinary microbiome during infection.NPJ biofilms and microbiomes · 2025Article
- ThermOptCobra: Thermodynamically optimal construction and analysis of metabolic networks for reliable phenotype predictions.iScience · 2025Article
- Yeast adapts to diverse ecological niches driven by genomics and metabolic reprogramming.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A personalized metabolic modelling approach through integrated analysis of RNA-Seq-based genomic variants and gene expression levels in Alzheimer's disease.Communications biology · 2025Article
- In silico encounters: harnessing metabolic modelling to understand plant-microbe interactions.FEMS microbiology reviews · 2025Review
- Wheels turning: CHO cell modeling moves into a digital biomanufacturing era: Subtitle: CHO Metabolic Modeling.Computational and structural biotechnology journal · 2025Review
- Driving towards digital biomanufacturing by CHO genome-scale models.Trends in biotechnology · 2024Review
- Article
- Genome-scale metabolic models applied for human health and biopharmaceutical engineering.Quantitative biology (Beijing, China) · 2023Review
- Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations.Briefings in bioinformatics · 2023Review
- From observational to actionable: rethinking omics in biologics production.Trends in biotechnology · 2023Review
- Ten quick tips for avoiding pitfalls in multi-omics data integration analyses.PLoS computational biology · 2023Article
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Abstract
Genome-scale metabolic models comprehensively describe an organism's metabolism and can be tailored using omics data to model condition-specific physiology. The quality of context-specific models is impacted by (i) choice of algorithm and parameters and (ii) alternate context-specific models that equally explain the -omics data. Here we quantify the influence of alternate optima on microbial and mammalian model extraction using GIMME, iMAT, MBA, and mCADRE. We find that metabolic tasks defining an organism's phenotype must be explicitly and quantitatively protected. The scope of alternate models is strongly influenced by algorithm choice and the topological properties of the parent genome-scale model with fatty acid metabolism and intracellular metabolite transport contributing much to alternate solutions in all models. mCADRE extracted the most reproducible context-specific models and models generated using MBA had the most alternate solutions. There were fewer qualitatively different solutions generated by GIMME in E. coli, but these increased substantially in the mammalian models. Screening ensembles using a receiver operating characteristic plot identified the best-performing models. A comprehensive evaluation of models extracted using combinations of extraction methods and expression thresholds revealed that GIMME generated the best-performing models in E. coli, whereas mCADRE is better suited for complex mammalian models. These findings suggest guidelines for benchmarking -omics integration algorithms and motivate the development of a systematic workflow to enumerate alternate models and extract biologically relevant context-specific models.
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