ArticlePLoS computational biology2015
Comparative Analysis of Yeast Metabolic Network Models Highlights Progress, Opportunities for Metabolic Reconstruction.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed.
- Coarse-Grained Modeling Elucidates Differential Metabolism ofACS synthetic biology · 2025Article
- Evolution and applications of genome-scale metabolic models in yeast systems biology studies.FEMS yeast research · 2025Review
- Emergence of Orchestrated and Dynamic Metabolism ofACS synthetic biology · 2024Article
- Integration of graph neural networks and genome-scale metabolic models for predicting gene essentiality.NPJ systems biology and applications · 2024Article
- The origins of the Guinness stout yeast.Communications biology · 2024Article
- Reconstruction of the genome-scale metabolic network model ofFrontiers in bioengineering and biotechnology · 2024Article
- Mitochondrial Metabolism in the Spotlight: Maintaining Balanced RNAP III Activity Ensures Cellular Homeostasis.International journal of molecular sciences · 2023Article
- Pareto optimal metabolic engineering for the growth-coupled overproduction of sustainable chemicals.Biotechnology and bioengineering · 2022Article
- Genome-scale modeling of yeast metabolism: retrospectives and perspectives.FEMS yeast research · 2022Review
- Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection.Molecular systems biology · 2021Article
- Tolerance to NADH/NADiScience · 2021Article
- Evaluating accessibility, usability and interoperability of genome-scale metabolic models for diverse yeasts species.FEMS yeast research · 2021Article
- Rare genetic variants affecting urine metabolite levels link population variation to inborn errors of metabolism.Nature communications · 2021Article
- Advances in biotechnological production of santalenes and santalols.Chinese herbal medicines · 2021Review
- CEG 2.0: an updated database of clusters of essential genes including eukaryotic organisms.Database : the journal of biological databases and curation · 2020Article
- Genetic buffering and potentiation in metabolism.PLoS computational biology · 2020Article
- Biotechnological production of betulinic acid and derivatives and their applications.Applied microbiology and biotechnology · 2020Review
- Into the wild: new yeast genomes from natural environments and new tools for their analysis.FEMS yeast research · 2020Review
- Article
- Metabolic fluxes-oriented control of bioreactors: a novel approach to tune micro-aeration and substrate feeding in fermentations.Microbial cell factories · 2019Article
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Abstract
We have compared 12 genome-scale models of the Saccharomyces cerevisiae metabolic network published since 2003 to evaluate progress in reconstruction of the yeast metabolic network. We compared the genomic coverage, overlap of annotated metabolites, predictive ability for single gene essentiality with a selection of model parameters, and biomass production predictions in simulated nutrient-limited conditions. We have also compared pairwise gene knockout essentiality predictions for 10 of these models. We found that varying approaches to model scope and annotation reflected the involvement of multiple research groups in model development; that single-gene essentiality predictions were affected by simulated medium, objective function, and the reference list of essential genes; and that predictive ability for single-gene essentiality did not correlate well with predictive ability for our reference list of synthetic lethal gene interactions (R = 0.159). We conclude that the reconstruction of the yeast metabolic network is indeed gradually improving through the iterative process of model development, and there remains great opportunity for advancing our understanding of biology through continued efforts to reconstruct the full biochemical reaction network that constitutes yeast metabolism. Additionally, we suggest that there is opportunity for refining the process of deriving a metabolic model from a metabolic network reconstruction to facilitate mechanistic investigation and discovery. This comparative study lays the groundwork for developing improved tools and formalized methods to quantitatively assess metabolic network reconstructions independently of any particular model application, which will facilitate ongoing efforts to advance our understanding of the relationship between genotype and cellular phenotype.
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