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Record W1985946189 · doi:10.2174/1389450003349362

The DNA Methylation Machinery as a Therapeutic Target

2000· review· en· W1985946189 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Drug Targets · 2000
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsMcGill University
FundersMcGill University
KeywordsDNA methylationBiologyDNA replicationComputational biologyEpigeneticsGeneDNAGeneticsGene expression

Abstract

fetched live from OpenAlex

Pharmacology and therapeutics have traditionally focused on altering the activity of specific proteins that play an important physiological role either to counteract disease processes or to achieve changes in physiology that are of benefit to the patient. The explosion in our understanding of gene expression programs opens up new horizons for pharmacological intervention. Key processes reversibly controlling genetic programs are attractive drug targets. DNA methylation is a fundamental feature of genomes and the control of their function and is therefore a candidate for pharmacological manipulation that might have important therapeutic advantage. This review argues that DNA methylation plays an important role in the control of genomic processes, suggests how the DNA methylation machinery is involved in cancer, identifies the enzymatic processes that are a target for drug intervention, proposes potential therapeutic utilities for agents that manipulate the DNA methylation machinery and discusses novel drugs that target the DNA methylation machinery.

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.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.344
Teacher spread0.315 · 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