An integrated global strategy for cell lysis, fractionation, enrichment and mass spectrometric analysis of phosphorylated peptides
Why this work is in the frame
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Bibliographic record
Abstract
Recently, the field of phosphoproteomics has progressed to the point where thousands of protein phosphorylations can be analyzed simultaneously and used to address significant biological questions. However, several challenges still exist in current LC-MS/MS-based phosphoproteomics methods. Among these are the increased dynamic range of phosphoproteomics samples (due to low stoichiometry of most protein phosphorylations), insufficient inhibition of phosphatase activity, and neutral losses which occur during phosphopeptide fragmentation by MS(n). Here we present an improved method, free of conventional phosphatase inhibitors, for sample treatment to minimize phosphatase activity and improve the efficiency of phosphopeptide enrichment. We also present a solution-based IEF method for phosphopeptide fractionation and explore the utility of various fragmentation methods for identifying phosphopeptides and localizing phosphorylation sites.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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