MétaCan
Menu
Back to cohort
Record W2522351964 · doi:10.1186/s13148-016-0268-4

The emerging role of lysine methyltransferase SETD8 in human diseases

2016· review· en· W2522351964 on OpenAlexfundno aff
Ciro Milite, Alessandra Feoli, Monica Viviano, Donatella Rescigno, Agostino Cianciulli, Amodio Luca Balzano, Antonello Mai, Sabrina Castellano, Gianluca Sbardella

Bibliographic record

VenueClinical Epigenetics · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsnot available
FundersMinistero dell’Istruzione, dell’Università e della RicercaEuropean Cooperation in Science and TechnologyYork UniversitySchool of Medicine, New York UniversityUniversità degli Studi di SalernoConstellation Pharmaceuticals
KeywordsMethyltransferaseHistone H4Histone methyltransferaseProliferating cell nuclear antigenHistoneBiologyLysineEpigeneticsCell biologyDNA replicationBiochemistryCell growthDNAMethylationGene

Abstract

fetched live from OpenAlex

SETD8/SET8/Pr-SET7/KMT5A is the only known lysine methyltransferase (KMT) that monomethylates lysine 20 of histone H4 (H4K20) in vivo. Lysine residues of non-histone proteins including proliferating cell nuclear antigen (PCNA) and p53 are also monomethylated. As a consequence, the methyltransferase activity of the enzyme is implicated in many essential cellular processes including DNA replication, DNA damage response, transcription modulation, and cell cycle regulation. This review aims to provide an overview of the roles of SETD8 in physiological and pathological pathways and to discuss the progress made to date in inhibiting the activity of SETD8 by small molecules, with an emphasis on their discovery, selectivity over other methyltransferases and cellular activity.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.044
GPT teacher head0.430
Teacher spread0.386 · 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

Citations105
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueClinical EpigeneticsSame topicEpigenetics and DNA MethylationFrench-language works237,207