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Record W1966852194 · doi:10.1093/nar/gkl1032

Global analysis of microRNA target gene expression reveals that miRNA targets are lower expressed in mature mouse and Drosophila tissues than in the embryos

2006· article· en· W1966852194 on OpenAlexafffund
Zhenbao Yu, Zhaofeng Jian, Shi‐Hsiang Shen, Enrico O. Purisima, Edwin Wang

Bibliographic record

VenueNucleic Acids Research · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsBiotechnology Research Institute
FundersNational Research Council Canada
KeywordsBiologymicroRNAEmbryoDrosophila (subgenus)GeneGene expressionGeneticsDrosophila melanogasterCell biologyDrosophilidaeRegulation of gene expressionMolecular biology

Abstract

fetched live from OpenAlex

MicroRNAs (miRNAs) are non-coding small RNAs of approximately 22 nt that regulate the gene expression by base pairing with target mRNAs, leading to mRNA cleavage or translational repression. It is currently estimated that miRNAs account for approximately 1% of predicted genes in higher eukaryotic genomes and that up to 30% of genes might be regulated by miRNAs. However, only very few miRNAs have been functionally characterized and the general functions of miRNAs are not globally studied. In this study, we systematically analyzed the expression patterns of miRNA targets using several public microarray profiles. We found that the expression levels of miRNA targets are lower in all mouse and Drosophila tissues than in the embryos. We also found miRNAs more preferentially target ubiquitously expressed genes than tissue-specifically expressed genes. These results support the current suggestion that miRNAs are likely to be largely involved in embryo development and maintaining of tissue identity.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.017
GPT teacher head0.300
Teacher spread0.283 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations111
Published2006
Admission routes2
Has abstractyes

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