Screening for Protein-Protein Interactions in the Yeast Two-Hybrid System
Bibliographic record
Abstract
The two-hybrid system (THS) () is a molecular genetic screen that detects protein-protein interactions. The protein specified by the yeast GAL4 gene activates the transcription of genes involved in galactose metabolism. It has two functional domains, a DNA binding domain, Gal4BD, and a transcriptional activating domain, Gal4AD, which interact with DNA sequences in the promoter regions of GAL1, GAL2, and GAL7 to stimulate transcription. The screen involves two plasmids; one carries the GAL4 BD sequence fused, in-frame, to a sequence coding for a “bait” protein, and the other carries GAL4 AD sequences, fused to “prey” sequences from a cDNA library. The two plasmids are introduced, typically by transformation, into a yeast strain carrying a reporter gene coupled to a GAL1, GAL2, or GAL7 promoter. If the proteins encoded by the bait and prey sequences interact to allow correct positioning of the Gal4AD and GaL4BD moieties, the reporter gene is activated. Transformants are plated on medium that allows the detection of reporter gene activation. The plasmid carrying the GAL4 AD :cDNA plasmid can be recovered, and the positive cDNA isolated and characterized.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.008 |
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".