Why Are There Still Over 1000 Uncharacterized Yeast Genes?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The yeast genetics community has embraced genomic biology, and there is a general understanding that obtaining a full encyclopedia of functions of the approximately 6000 genes is a worthwhile goal. The yeast literature comprises over 40,000 research papers, and the number of yeast researchers exceeds the number of genes. There are mutated and tagged alleles for virtually every gene, and hundreds of high-throughput data sets and computational analyses have been described. Why, then, are there >1000 genes still listed as uncharacterized on the Saccharomyces Genome Database, 10 years after sequencing the genome of this powerful model organism? Examination of the currently uncharacterized gene set suggests that while some are small or newly discovered, the vast majority were evident from the initial genome sequence. Most are present in multiple genomics data sets, which may provide clues to function. In addition, roughly half contain recognizable protein domains, and many of these suggest specific metabolic activities. Notably, the uncharacterized gene set is highly enriched for genes whose only homologs are in other fungi. Achieving a full catalog of yeast gene functions may require a greater focus on the life of yeast outside the laboratory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it