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Record W2006583056 · doi:10.4161/trla.24557

Re-analysis of genome wide data on mammalian microRNA-mediated suppression of gene expression

2013· article· en· W2006583056 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

VenueTranslation · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsMcGill Genome CentreMcGill University and Génome Québec Innovation Centre
FundersCancerfondenCancerföreningen i StockholmVetenskapsrådetKarolinska InstitutetSwedish Cancer FoundationUniversity of California, DavisMcGill University
KeywordsmicroRNAMessenger RNATranslation (biology)BiologyGene expressionGeneRNARegulation of gene expressionGeneticsMolecular biologyCell biology

Abstract

fetched live from OpenAlex

microRNAs are short endogenously expressed RNAs that regulate gene expression post-transcriptionally. Although both mRNA degradation and suppression of mRNA translation can mediate reduced protein levels following microRNA targeting of an mRNA, their relative contributions have remained elusive. A recent genome-wide study in mammals employing RNA-sequencing to measure microRNA effects on mRNA translation and stability concluded that 84-89% of microRNA-induced suppression of gene expression is due to degradation of target mRNAs. We re-analyzed this data set and applied a number of analysis modifications which revealed that the contribution of mRNA translation was likely underestimated for some mRNA subsets. Moreover, in contrast to the original analysis, our analysis indicated that suppression of mRNA translation precedes mRNA degradation upon microRNA targeting. Our findings thereby enhance our understanding of microRNA mediated genome wide suppression of gene expression in mammals.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.024
GPT teacher head0.265
Teacher spread0.241 · 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