A Systematic Approach for the Genetic Dissection of Protein Complexes in Living Cells
Bibliographic record
Abstract
Cells contain many important protein complexes involved in performing and regulating structural, metabolic, and signaling functions. One major challenge in cell biology is to elucidate the organization and mechanisms of robustness of these complexes in vivo. We developed a systematic approach to study structural dependencies within complexes in living cells by deleting subunits and measuring pairwise interactions among other components. We used our methodology to perturb two conserved eukaryotic complexes: the retromer and the nuclear pore complex. Our results identify subunits that are critical for the assembly of these complexes, reveal their structural architecture, and uncover mechanisms by which protein interactions are modulated. Our results also show that paralogous proteins play a key role in the robustness of protein complexes and shape their assembly landscape. Our approach paves the way for studying the response of protein interactomes to mutations and enhances our understanding of genotype-phenotype maps.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".