Phosphoproteomics—finally fulfilling the promise?
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
Networks of protein-protein and protein-metabolite interactions are commonly found in biological systems where signals must be passed from one location or component within a cell to another, such as from a receptor on the plasma membrane to a transcription factor in the nucleus. Regulation of such networks, or signal transduction pathways, is often achieved by transient, reversible modification of the components involved. Several types of post-translational modifications of proteins are employed in signal transduction including ubiquitylation of lysines and palmitoylation of cysteines, but by far the best appreciated and apparently the most important involves phosphorylation of serine, threonine and tyrosine residues. Whilst protein phosphorylation has long been recognized as functionally important, low stoichiometry has ultimately impeded global analyses (phosphoproteomics). Recent developments in the application of metal oxide chromatography and advanced mass spectrometric techniques have enabled phosphoproteomics to move beyond mere proof-of-principle experiments, to the stage where it can successfully address complex biological questions. Here we cover the development of phosphopeptide/protein analysis by mass spectrometry and the various techniques used to enrich phosphopeptides/proteins. We also speculate on the future of phosphoproteomic research, now that the goal of generating global phosphoproteomic datasets has been realized.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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