Evidence map›Paper›PMID 35094064›Full record

ReviewFEMS yeast research2022

Genome-scale modeling of yeast metabolism: retrospectives and perspectives.

Yu Chen, Feiran Li, Jens Nielsen

Abstract readReview
In one paragraph

Review in FEMS yeast research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed.

  1. Review
  2. Reconstruction of human metabolic models with large language models.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Review
  4. Review
  5. Article
  6. 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 · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Robust Prediction of Enzyme Variant Kinetics with RealKcat.bioRxiv : the preprint server for biology · 2025
    Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yu ChenDepartment of Biology and Biological Engineering, Chalmers University of Technology, SE412 96 Gothenburg, Sweden.ORCID 0000-0003-3326-9068
Feiran LiDepartment of Biology and Biological Engineering, Chalmers University of Technology, SE412 96 Gothenburg, Sweden.ORCID 0000-0001-9155-5260
Jens NielsenDepartment of Biology and Biological Engineering, Chalmers University of Technology, SE412 96 Gothenburg, Sweden.ORCID 0000-0002-9955-6003

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Yeasts have been widely used for production of bread, beer and wine, as well as for production of bioethanol, but they have also been designed as cell factories to produce various chemicals, advanced biofuels and recombinant proteins. To systematically understand and rationally engineer yeast metabolism, genome-scale metabolic models (GEMs) have been reconstructed for the model yeast Saccharomyces cerevisiae and nonconventional yeasts. Here, we review the historical development of yeast GEMs together with their recent applications, including metabolic flux prediction, cell factory design, culture condition optimization and multi-yeast comparative analysis. Furthermore, we present an emerging effort, namely the integration of proteome constraints into yeast GEMs, resulting in models with improved performance. At last, we discuss challenges and perspectives on the development of yeast GEMs and the integration of proteome constraints.

Indexed as

Metabolic EngineeringSaccharomyces cerevisiaeBiofuelsProteomeRetrospective StudiesBiofuelsProteomeconstraint-based modelinggenome-scale metabolic modelmetabolic engineeringproteome constraints

Identifiers

PMID35094064
PMCPMC8862083

What OpenQuestion holds

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Registered trials

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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.