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New insights into riboswitch regulation mechanisms

2011· review· en· W2156878320 on OpenAlexafffund
Laurène Bastet, Audrey Dubé, Éric Massé, Daniel A. Lafontaine

Bibliographic record

VenueMolecular Microbiology · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health ResearchUniversité de Sherbrooke
KeywordsBiologyRiboswitchComputational biologyEvolutionary biologyGeneticsRNANon-coding RNAGene

Abstract

fetched live from OpenAlex

Riboswitches are genetic elements located in non-coding regions of some messenger RNAs (mRNAs) that are present in all three domains of life. The binding of ligands to riboswitches induces conformational changes in the mRNA molecule, resulting in modulation of gene transcription, or RNA splicing, translation or stability. This mechanism of regulation is particularly widespread in bacteria and allows a direct response to various metabolic changes. A large number of riboswitches have been discovered in the last few years, suggesting the existence of a huge diversity of regulatory ligands and genetic mechanisms of regulation. This review focuses on recent discoveries in riboswitch regulatory mechanisms as well as current outstanding challenges.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.016
GPT teacher head0.254
Teacher spread0.238 · 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

Citations79
Published2011
Admission routes2
Has abstractyes

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