Large Scale Investigation in Yeast, to Identify Novel Gene(s) Involved in Translation Pathway
Bibliographic record
Abstract
As a fundamental step in the gene expression pathway, protein synthesis (also known as translation) plays a crucial role in the biology of a cell.Although much has been discovered about the translation pathway over the last few decades, the list of novel factors affecting the translation pathway continues to grow indicating the presence of other novel players associated with the protein synthesis pathway which are yet to be discovered.This study aimed to identify novel genes involved in the translation pathway.To this end, we used a variety of large-scale screening techniques followed by low throughput experimental analyses designed for genetic studies in yeast, Saccharomyces cerevisiae.Using molecular biology techniques and bioinformatics, we systematically investigated the effect of specific gene deletions on translation fidelity and efficiency, Internal Ribosome Entry Sites (IRESs) functionality and translation-related helicase activities, for a total of ~ 70,000 strain analysis.We further studied the activity of ~15 genes in more details for their involvement in translation pathway.In light of the current study we propose that there remain other uncharacterized factors that influence translation regulation.Further investigations to characterize these novel factors are recommended.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".