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Record W3020988352 · doi:10.3390/ijms21093354

Therapeutic Targeting of the General RNA Polymerase II Transcription Machinery

2020· review· en· W3020988352 on OpenAlexafffund
Ryan Martin, Terence E. Hébert, Jason C. Tanny

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsRNA polymerase IITranscription (linguistics)PolymeraseBiologyRNA polymeraseTranscription preinitiation complexComputational biologyTranscription factorCell biologyRNACancer researchGeneticsGene expressionPromoterDNAGene

Abstract

fetched live from OpenAlex

Inhibitors targeting the general RNA polymerase II (RNAPII) transcription machinery are candidate therapeutics in cancer and other complex diseases. Here, we review the molecular targets and mechanisms of action of these compounds, framing them within the steps of RNAPII transcription. We discuss the effects of transcription inhibitors in vitro and in cellular models (with an emphasis on cancer), as well as their efficacy in preclinical and clinical studies. We also discuss the rationale for inhibiting broadly acting transcriptional regulators or RNAPII itself in complex diseases.

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 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 score0.956
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.017
GPT teacher head0.298
Teacher spread0.281 · 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.

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

Citations54
Published2020
Admission routes2
Has abstractyes

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