Protein-Fragment Complementation Assays for Large-Scale Analysis, Functional Dissection, and Spatiotemporal Dynamic Studies of Protein–Protein Interactions in Living Cells
Bibliographic record
Abstract
Protein-fragment complementation assays (PCAs) comprise a family of assays that can be used to study protein-protein interactions (PPIs), conformation changes, and protein complex dimensions. We developed PCAs to provide simple and direct methods for the study of PPIs in any living cell, subcellular compartments or membranes, multicellular organisms, or in vitro. Because they are complete assays, requiring no cell-specific components other than reporter fragments, they can be applied in any context. PCAs provide a general strategy for the detection of proteins expressed at endogenous levels within appropriate subcellular compartments and with normal posttranslational modifications, in virtually any cell type or organism under any conditions. Here we introduce a number of applications of PCAs in budding yeast, Saccharomyces cerevisiae These applications represent the full range of PPI characteristics that might be studied, from simple detection on a large scale to visualization of spatiotemporal dynamics.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".