High throughput strategies for probing the different organizational levels of protein interaction networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Most proteins do not exist as isolated molecules in the cell, but instead serve as nodes of protein interaction networks. A number of techniques have been developed in the last two decades to study protein interaction networks at different levels of detail. Here we describe some of the techniques for characterizing protein interactions and protein complexes on a system-wide scale, focusing especially on newly emerging techniques that use co-migration. These newer approaches have the advantage that no genetic manipulation is necessary, thereby allowing investigation of protein complexes at their endogenous levels in the correct cellular context. Finally, we discuss different approaches for measuring large-scale temporal changes to protein interaction networks, an area that we believe will be one of the frontiers in systems biology in the coming years.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it