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Epigenetics and Complex Disease: From Etiology to New Therapeutics

2007· review· en· W2135812015 on OpenAlexaff
Carolyn Ptak, Artūras Petronis

Bibliographic record

VenueThe Annual Review of Pharmacology and Toxicology · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsCentre for Addiction and Mental Health
FundersNational Institute of Mental Health
KeywordsEpigeneticsDiseaseBioinformaticsEpigenesisMedicineEpigenetic therapyComputational biologyBiologyNeuroscienceDNA methylationGeneticsPathologyGene

Abstract

fetched live from OpenAlex

Epigenetics is a new development in complex non-Mendelian disease, which may not only uncover etiologic and pathogenic mechanisms but may also provide the basis for the development of medications that would target the primary epigenetic causes of such diseases. Such epigenetic drugs would be novel, potentially possessing substantially higher therapeutic potential and a much lower rate of adverse effects in comparison to current symptomatic treatments. A collection of epigenetic drugs already exist at various stages of development and, although their effectiveness has yet to be maximized, they show great promise in the treatment of cancer, psychiatric disorders, and other complex diseases. Here we present a review of the epigenetic theory of complex disease and an evaluation of current epigenetic therapies, as well as predictions of the future directions in this expanding field.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.071
GPT teacher head0.427
Teacher spread0.356 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations167
Published2007
Admission routes1
Has abstractyes

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