Mass Spectrometry-Based Structural Proteomics
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
Structural proteomics is the application of protein chemistry and modern mass spectrometric techniques to problems such as the characterization of protein structures and assemblies and the detailed determination of protein-protein interactions. The techniques used in structural proteomics include crosslinking, photoaffinity labeling, limited proteolysis, chemical protein modification and hydrogen/deuterium exchange, all followed by mass spectrometric analysis. None of these methods alone can provide complete structural information, but a "combination" of these complementary approaches can be used to provide enough information for answering important biological questions. Structural proteomics can help to determine, for example, the detailed structure of the interfaces between proteins that may be important drug targets and the interactions between proteins and ligands. In this review, we have tried to provide a brief overview of structural proteomics methodologies, illustrated with examples from our laboratory and from the literature.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 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