ArticleNature communications2021
A genome-scale metabolic model of Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
46 citing papers in PubMed.
- Dynamic, model-guided intensification of fuel ethanol production in yeast: proteome constraints, CRISPR rewiring, and high-gravity fermentations.Archives of microbiology · 2026Review
- Towards the construction of a virtual yeast.Nature · 2026Review
- Model-driven analysis reveals oxidative stress adaptation enabling efficient energy utilization in a Crabtree-negative Saccharomyces cerevisiae.Scientific reports · 2026Article
- Integrated multi-dimensional modeling of non-model bacteria identifies engineering targets for acarbose biosynthesis optimization.Cell reports methods · 2026Article
- Selecting methods for draft GEM generation in multicellular eukaryotes: a comparative analysis.BMC bioinformatics · 2026Article
- The return of metabolism: biochemistry and physiology of glycolysis.Biological reviews of the Cambridge Philosophical Society · 2026Review
- Systems biology of yeast metabolism.FEMS yeast research · 2026Review
- The Power of Yeast.Yeast (Chichester, England) · 2025Review
- Integrative Thermodynamic Strategies in Microbial Metabolism.International journal of molecular sciences · 2025Article
- Article
- The Dawn of High-Throughput and Genome-Scale Kinetic Modeling: Recent Advances and Future Directions.ACS synthetic biology · 2025Review
- ThermOptCobra: Thermodynamically optimal construction and analysis of metabolic networks for reliable phenotype predictions.iScience · 2025Article
- A modular model integrating metabolism, growth, and cell cycle predicts that fermentation is required to modulate cell size in yeast populations.PLoS computational biology · 2025Article
- Coarse-Grained Modeling Elucidates Differential Metabolism ofACS synthetic biology · 2025Article
- New insights in metabolism modelling to decipher plant-microbe interactions.The New phytologist · 2025Review
- Evolution and applications of genome-scale metabolic models in yeast systems biology studies.FEMS yeast research · 2025Review
- Ecological design of high-performance synthetic microbial communities: from theoretical foundations to functional optimization.ISME communications · 2025Review
- Integration of metabolomics and other omics: from microbes to microbiome.Applied microbiology and biotechnology · 2024Review
- Yeast9: a consensus genome-scale metabolic model for S. cerevisiae curated by the community.Molecular systems biology · 2024Article
- Mitochondrial ATP generation is more proteome efficient than glycolysis.Nature chemical biology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Eukaryotic organisms play an important role in industrial biotechnology, from the production of fuels and commodity chemicals to therapeutic proteins. To optimize these industrial systems, a mathematical approach can be used to integrate the description of multiple biological networks into a single model for cell analysis and engineering. One of the most accurate models of biological systems include Expression and Thermodynamics FLux (ETFL), which efficiently integrates RNA and protein synthesis with traditional genome-scale metabolic models. However, ETFL is so far only applicable for E. coli. To adapt this model for Saccharomyces cerevisiae, we developed yETFL, in which we augmented the original formulation with additional considerations for biomass composition, the compartmentalized cellular expression system, and the energetic costs of biological processes. We demonstrated the ability of yETFL to predict maximum growth rate, essential genes, and the phenotype of overflow metabolism. We envision that the presented formulation can be extended to a wide range of eukaryotic organisms to the benefit of academic and industrial research.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.