Linking the kinome and phosphorylome—a comprehensive review of approaches to find kinase targets
Why this work is in the frame
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Bibliographic record
Abstract
Protein phosphorylation is associated with most cell signaling and developmental processes in eukaryotes. Despite the vast extent of the phosphoproteome within the cell, connecting specific kinases with relevant targets remains a significant experimental frontier. The challenge of linking kinases and their substrates reflects the complexity of kinase function. For example, kinases tend to exert their biological effects through supernumerary, redundant phosphorylation, often on multiple protein complex components. Although these types of phosphorylation events are biologically significant, those kinases responsible are often difficult to identify. Recent methods for global analysis of protein phosphorylation promise to substantially accelerate efforts to map the dynamic phosphorylome. Here, we review both conventional methods to identify kinase targets and more comprehensive genomic and proteomic approaches to connect the kinome and phosphorylome.
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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) | 0.002 | 0.000 |
| 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 | 0.000 | 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