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Record W2396562999 · doi:10.1385/1-59259-823-4:065

Assay for Evaluating Ribonuclease H-Mediated Degradation of RNA–Antisense Oligonucleotide Duplexes

2004· article· en· W2396562999 on OpenAlexaff
Annie Galarneau, Kyung‐Lyum Min, Maria Mangos, Masad J. Damha

Bibliographic record

VenueHumana Press eBooks · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsMcGill University
Fundersnot available
KeywordsRNAOligonucleotideRibonucleaseDNAComputational biologyRNase HEnzymeBiochemistryChemistryDuplex (building)BiologyMolecular biologyRNase PGene

Abstract

fetched live from OpenAlex

Ribonucleases H are complex enzymes whose functions are not clearly understood, further compounded by the fact that multiple forms of the enzyme are present in various organisms. They are known to recognize and degrade the ribonucleic acid (RNA) strand of numerous deoxyribonucleic acid (DNA)-RNA duplex substrates, and so may provide a unique mode of therapeutic intervention at the genetic level of virtually any disease. We have therefore set out detailed procedures for conducting routine assays with almost any one of this family of enzymes by a straightforward assay aimed at identifying novel enzyme-activating antisense oligonucleotides (AONs). The procedures described herein should enable easy identification of potent AON molecules, provided that the RNA is appropriately labeled for subsequent visualization following the guidelines set forth in this protocol.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.042
GPT teacher head0.300
Teacher spread0.258 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations10
Published2004
Admission routes1
Has abstractyes

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