Regulation of biological processes by ubiquitin ligases: a focus on the Pagano Lab’s contribution
Bibliographic record
Abstract
Protein homeostasis depends on many fundamental processes including mRNA synthesis, translation, post-translational modifications, and proteolysis. In the late 70s and early 80s the discovery that the small 76 amino acid protein ubiquitin could be attached to target proteins via a multi-stage process involving ubiquitin-activating enzymes, ubiquitin conjugating enzymes, and ubiquitin ligases, revealed an exciting new post-translational mechanism to regulate protein degradation. This cellular system was uncovered using biochemical methods by Avram Hershko, who would later won the Nobel prize for this discovery; however, the biological functions of ubiquitin ligases remained unknown for many years. It was initially described that ubiquitin modifies proteins at one or more lysine residues and once a long ubiquitin chain was assembled, proteins were degraded by the proteasome. Now we know that proteins can be mono-, multimono-, homotypic poly-, or heterotypic poly-ubiquitylated, each of which confers a specific signal that goes beyond protein degradation regulating additional key cellular functions such as signal transduction, protein localization, recognition of damaged proteins, etc.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| 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".