Examining protein–protein interactions using endogenously tagged yeast arrays: The Cross-and-Capture system
Bibliographic record
Abstract
Comprehensive approaches to detect protein-protein interactions (PPIs) have been most successful in the yeast model system. Here we present "Cross-and-Capture," a novel assay for rapid, sensitive assessment of PPIs via pulldown of differently tagged yeast strain arrays. About 500 yeast genes that function in DNA replication, repair, and recombination and nuclear proteins of unknown function were chromosomally tagged with six histidine residues or triple VSV epitopes. We demonstrate that the assay can interrogate a wide range of previously known protein complexes with increased resolution and sensitivity. Furthermore, we use "Cross-and-Capture" to identify two novel protein complexes: Rtt101p-Mms1p and Sae2p-Mre11p. The Rtt101p-Mms1p interaction was subsequently characterized by genetic and functional analyses. Our studies establish the "Cross-and-Capture" assay as a novel, versatile tool that provides a valuable complement for the next generation of yeast proteomic studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".