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DNA methylation‐mediated nucleosome dynamics and oncogenic Ras signaling

2008· review· en· W1590090143 on OpenAlexafffund
Samir Kumar Patra, Moshe Szyf

Bibliographic record

VenueFEBS Journal · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsMcGill University
FundersNational Cancer InstituteUniversity of CalcuttaCanadian Institute for Advanced Research
KeywordsDNA methylationNucleosomeDNACancer researchDynamics (music)Cell biologyHistoneChemistryBiologyGeneticsPsychologyGeneGene expression

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.306
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations40
Published2008
Admission routes2
Has abstractyes

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