Bibliographic record
Abstract
Phosphorylation sites are formed by protein kinases ('writers'), frequently exert their effects following recognition by phospho-binding proteins ('readers') and are removed by protein phosphatases ('erasers'). This writer-reader-eraser toolkit allows phosphorylation events to control a broad range of regulatory processes, and has been pivotal in the evolution of new functions required for the development of multi-cellular animals. The proteins that comprise this system of protein kinases, phospho-binding targets and phosphatases are typically modular in organization, in the sense that they are composed of multiple globular domains and smaller peptide motifs with binding or catalytic properties. The linkage of these binding and catalytic modules in new ways through genetic recombination, and the selection of particular domain combinations, has promoted the evolution of novel, biologically useful processes. Conversely, the joining of domains in aberrant combinations can subvert cell signalling and be causative in diseases such as cancer. Major inventions such as phosphotyrosine (pTyr)-mediated signalling that flourished in the first multi-cellular animals and their immediate predecessors resulted from stepwise evolutionary progression. This involved changes in the binding properties of interaction domains such as SH2 and their linkage to new domain types, and alterations in the catalytic specificities of kinases and phosphatases. This review will focus on the modular aspects of signalling networks and the mechanism by which they may have evolved.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".