Evidence map›Paper›PMID 40874759›Full record

ReviewFEMS yeast research2025

Evolution and applications of genome-scale metabolic models in yeast systems biology studies.

Xiaodan He, Hongzhong Lu

Abstract readReview
In one paragraph

Review in FEMS yeast research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
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

2 authors.

Xiaodan HeState Key Laboratory of Microbial Metabolism, School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, P. R. China.ORCID 0009-0004-1106-4306
Hongzhong LuState Key Laboratory of Microbial Metabolism, School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, P. R. China.

Funding

National Key Research and Development Program of China 22208211National Key Research and Development Program of China 22378263National Natural Science Foundation of ChinaShanghai Municipal Science and Technology Commission 2022YFA0913000
6 · The paper itself

Abstract

Genome-scale metabolic models (GEMs) can be used to simulate the metabolic network of an organism in a systematic and holistic way. Different yeast species, including Saccharomyces cerevisiae, have emerged as powerful cell factories for bioproduction. Recently, with the dedicated efforts from the scientific community, significant progress has been made in the development of yeast GEMs. Numerous versions of yeast GEMs and the derived multiscale models have been released, facilitating integrative omics analysis and rational strain design for different types of yeast cell factories. These advancements reflected the evolution and maturation of yeast GEMs together with a model ecosystem around them. This review will summarize the development and expansion of yeast GEMs and discuss their applications in yeast systems biology studies. It is anticipated that yeast GEMs will continue to play an increasingly important role in pioneering yeast physiological and metabolic studies in coming years.

Indexed as

Genome, FungalMetabolic Networks and PathwaysModels, BiologicalSaccharomyces cerevisiaeSystems Biologybig data analysisgenome-scale metabolic modelsmetabolic engineeringyeast

Identifiers

PMID40874759
PMCPMC12509835

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.