DNA methylation‐mediated nucleosome dynamics and oncogenic Ras signaling
Bibliographic record
Abstract
Cytosine methylation at the 5-carbon position is the only known stable base modification found in the mammalian genome. The organization and modification of chromatin is a key factor in programming gene expression patterns. Recent findings suggest that DNA methylation at the junction of transcription initiation and elongation plays a critical role in suppression of transcription. This effect is mechanistically mediated by the state of chromatin modification. DNA methylation attracts binding of methyl-CpG-binding domain proteins that trigger repression of transcription, whereas DNA demethylation facilitates transcription activation. Understanding the rules that guide differential gene expression, as well as transcription dynamics and transcript abundance, has proven to be a taxing problem for molecular biologists and oncologists alike. The use of novel molecular modeling methods is providing exciting insights into the challenging problem of how methylation mediates chromatin dynamics. New data implicate lipid rafts as the coordinators of signals emanating from the cell membrane and are converging on the mechanisms linking DNA methylation and chromatin dynamics. This review focuses on some of these recent advances and uses lipid-raft-facilitated Ras signaling as a paradigm for understanding DNA methylation, chromatin dynamics and apoptosis.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".