ArticleNature communications2020
Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Reconstruction of human metabolic models with large language models.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- The return of metabolism: biochemistry and physiology of glycolysis.Biological reviews of the Cambridge Philosophical Society · 2026Review
- In silico analysis and comparison of the metabolic capabilities of different organisms by reducing metabolic complexity.Microbiome · 2026Article
- TidyMass2: advancing LC-MS untargeted metabolomics through metabolite origin inference and metabolic feature-based functional module analysis.Nature communications · 2026Article
- Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine.PLoS computational biology · 2025Article
- Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025Review
- Pseudomonas aeruginosa faces a fitness trade-off between mucosal colonization and antibiotic tolerance during airway infection.Nature microbiology · 2024Article
- Host cell CRISPR genomics and modelling reveal shared metabolic vulnerabilities in the intracellular development of Plasmodium falciparum and related hemoparasites.Nature communications · 2024Article
- PGENature · 2024Article
- Mathematical reconstruction of the metabolic network in an in-vitro multiple myeloma model.PLoS computational biology · 2023Article
- Dynamic partitioning of branched-chain amino acids-derived nitrogen supports renal cancer progression.Nature communications · 2022Article
- The hidden simplicity of metabolic networks is revealed by multireaction dependencies.Science advances · 2022Article
- Machine learning-guided evaluation of extraction and simulation methods for cancer patient-specific metabolic models.Computational and structural biotechnology journal · 2022Article
- Thermodynamic Genome-Scale Metabolic Modeling of Metallodrug Resistance in Colorectal Cancer.Cancers · 2021Article
- Modular dynamic biomolecular modelling with bond graphs: the unification of stoichiometry, thermodynamics, kinetics and data.Journal of the Royal Society, Interface · 2021Article
- TCA Cycle and Its Relationship with Clavulanic Acid Production: A Further Interpretation by Using a Reduced Genome-Scale Metabolic Model ofBioengineering (Basel, Switzerland) · 2021Article
- Reaction lumping in metabolic networks for application with thermodynamic metabolic flux analysis.Scientific reports · 2021Article
- Quantifying the roles of space and stochasticity in computer simulations for cell biology and cellular biochemistry.Molecular biology of the cell · 2021Article
- A Graph-Based Framework for Multiscale Modeling of Physiological Transport.Frontiers in network physiology · 2021Review
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Altered metabolism is associated with many human diseases. Human genome-scale metabolic models (GEMs) were reconstructed within systems biology to study the biochemistry occurring in human cells. However, the complexity of these networks hinders a consistent and concise physiological representation. We present here redHUMAN, a workflow for reconstructing reduced models that focus on parts of the metabolism relevant to a specific physiology using the recently established methods redGEM and lumpGEM. The reductions include the thermodynamic properties of compounds and reactions guaranteeing the consistency of predictions with the bioenergetics of the cell. We introduce a method (redGEMX) to incorporate the pathways used by cells to adapt to the medium. We provide the thermodynamic curation of the human GEMs Recon2 and Recon3D and we apply the redHUMAN workflow to derive leukemia-specific reduced models. The reduced models are powerful platforms for studying metabolic differences between phenotypes, such as diseased and healthy cells.
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