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Record W2789202735 · doi:10.1186/s13048-018-0381-4

Circular RNAs: biogenesis, expression and their potential roles in reproduction

2018· review· en· W2789202735 on OpenAlexafffund
Guobo Quan, Julang Li

Bibliographic record

VenueJournal of Ovarian Research · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCircular RNAs in diseases
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilQingdao Agricultural University
KeywordsBiogenesisBiologyCircular RNARNAContext (archaeology)Competing endogenous RNARNA splicingRNase PCell biologyComputational biologyRibonuclease IIIRibonucleaseLong non-coding RNAMicrovesiclesGeneticsmicroRNARNA interferenceGene

Abstract

fetched live from OpenAlex

Unlike other non-coding RNAs (ncRNAs), circular RNA (circRNA) is generally presented as a covalently linked circle lacking both a 5' cap and a 3' tail. circRNAs were thought to be spliced intermediates, byproducts, or products of abnormal RNA splicing events. However, the high-throughput sequencing technology coupled with bioinformatics has recently uncovered thousands of endogenous circRNAs in cells of many different species. These circRNAs show various features, such as abundant expression, evolutionary conservation, cell- or tissue-specific expression, and a higher resistance to degradation caused by exonuclease or ribonuclease (RNase), suggesting their potentially biological significance. However, the function of these circRNAs, their mechanism of action, and the regulation of their biogenesis and degradation remains largely unclear. The current research and findings of circRNA in the context of reproduction will be reviewed. Additionally, the perspectives of circRNAs in the field will be discussed.

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)0.001
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.069
GPT teacher head0.388
Teacher spread0.320 · 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

Citations106
Published2018
Admission routes2
Has abstractyes

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Same venueJournal of Ovarian ResearchSame topicCircular RNAs in diseasesFrench-language works237,207