Bibliographic record
Abstract
Microbial ester kinases identified in the past 3 decades came as a surprise, as protein phosphorylation on Ser, Thr, and Tyr amino acids was thought to be unique to eukaryotes. Current analysis of available microbial genomes reveals that "eukaryote-like" protein kinases are prevalent in prokaryotes and can converge in the same signaling pathway with the classical microbial "two-component" systems. Most microbial tyrosine kinases lack the "eukaryotic" Hanks domain signature and are designated tyrosine kinases based upon their biochemical activity. These include the tyrosine kinases termed bacterial tyrosine kinases (BY-kinases), which are responsible for the majority of known bacterial tyrosine phosphorylation events. Although termed generally as bacterial tyrosine kinases, BY-kinases can be considered as one family belonging to the superfamily of prokaryotic protein-tyrosine kinases in bacteria. Other members of this superfamily include atypical "odd" tyrosine kinases with diverse mechanisms of protein phosphorylation and the "eukaryote-like" Hanks-type tyrosine kinases. Here, we discuss the distribution, phylogeny, and function of the various prokaryotic protein-tyrosine kinases, focusing on the recently discovered Mycobacterium tuberculosis PtkA and its relationship with other members of this diverse family of proteins.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".