Single-Molecule Resolution Fluorescent In Situ Hybridization (smFISH) in the Yeast S. cerevisiae
Bibliographic record
Abstract
Regulating gene expression is a major task for all cellular systems. RNA production and degradation plays a critical role in this process and accurately measuring cellular mRNA levels is essential to understanding gene expression regulation. Classical biochemical assays that study gene expression rely on extracting RNAs from large populations of cells, taking them out of their native context and thereby losing spatial information as well as cell-to-cell variability. In this chapter, we describe a fluorescent in situ hybridization (FISH) technique that circumvents this problem by detecting single RNAs in single cells. The technique employs multiple single-stranded short DNA probes fluorescently labeled with organic dyes that hybridize to target RNAs in fixed cells, allowing quantification and localization of RNAs at the single-cell level and at single-molecule resolution. The protocol described here has been optimized for the yeast S. cerevisiae.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".