Functional Genomics Using the <i>Saccharomyces cerevisiae</i> Yeast Deletion Collections
Bibliographic record
Abstract
Constructed by a consortium of 16 laboratories, the Saccharomyces genome-wide deletion collections have, for the past decade, provided a powerful, rapid, and inexpensive approach for functional profiling of the yeast genome. Loss-of-function deletion mutants were systematically created using a polymerase chain reaction (PCR)-based gene deletion strategy to generate a start-to-stop codon replacement of each open reading frame by homologous recombination. Each strain carries two molecular barcodes that serve as unique strain identifiers, enabling their growth to be analyzed in parallel and the fitness contribution of each gene to be quantitatively assessed by hybridization to high-density oligonucleotide arrays or through the use of next-generation sequencing technologies. Functional profiling of the deletion collections, using either strain-by-strain or parallel assays, provides an unbiased approach to systematically survey the yeast genome. The Saccharomyces yeast deletion collections have proved immensely powerful in contributing to the understanding of gene function, including functional relationships between genes and genetic pathways in response to diverse genetic and environmental perturbations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".