Why is Yeast Such a Widely Used Eukaryotic Model Organism? A Literature Review
Bibliographic record
Abstract
Introduction: The use of yeasts in various fields dates back to thousands of years ago, but their biological significance has only recently been discovered. Genomes of many members of this relatively small group have been sequenced, and the consequent studies on them and on various cell processes have revealed similarities between yeast species Saccharomyces cerevisiae and Schizosaccharomyces pombe, and other eukaryotes, suggesting that they may be used as eukaryotic model organisms. Methods: A literature search was conducted investigating general yeast characteristics, genetics and physiology, as well as modern applications in biomedical research as model organisms. Results: Yeasts have many traits that make them especially favorable in research: they can easily be cultivated in laboratory conditions where their metabolism may be altered by tweaking the growth medium properties. Additionally, analyzing the yeast and human genome sequences has revealed astonishing similarities, with many successfully mapped homologous genes. Discussion: By varying environmental conditions of a S. cerevisiae culture, it was found that such treatments could affect respiration in yeast. Proving useful in research of antifungal drugs and interactions between fungal pathogens and hosts, yeast was also used as a model for studying prion related diseases, Alzheimer’s disease and cancer, amongst others. Conclusion: With all the yeast characteristics—their simple requirements for growth, their genome and metabolism similar to other eukaryotes, and their use in studying varying disease conditions—it is understandable and clear why yeasts are such widely used model organisms. Considering recent advancements, their application in biomedical research will inevitably increase over time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".