The complex interactions of p53 with target DNA: we learn as we go
Bibliographic record
Abstract
The most import biological function of the tumor suppressor p53 is that of a sequence-specific transactivator. In response to a variety of cellular stress stimuli, p53 induces the transcription of an ever-increasing number of target genes, leading to growth arrest and repair, or to apoptosis. Long considered as a "latent" DNA binder that requires prior activation by C-terminal modification, recent data provide strong evidence that the DNA binding activity of p53 is strongly dependent on structural features within the target DNA and is latent only if the target DNA lacks a certain structural signal code. In this review we discuss evidence for complex interactions of p53 with DNA, which are strongly dependent on the dynamics of DNA structure, especially in the context of chromatin. We provide a model of how this complexity may serve to achieve selectivity of target gene regulation by p53 and how DNA structure in the context of chromatin may serve to modulate p53 functions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".