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Record W2049865059 · doi:10.4161/rna.7.3.11649

Crossing the borders: Poly(A)-binding proteins working on both sides of the fence

2010· review· en· W2049865059 on OpenAlexafffund
Jean‐François Lemay, Caroline Lemieux, Olivier St-André, François Bachand

Bibliographic record

VenueRNA Biology · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Structural Characterization
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsFence (mathematics)BiologyDNA-binding proteinPlasma protein bindingCell biologyComputational biologyGeneticsEvolutionary biologyTranscription factorGeneEngineering

Abstract

fetched live from OpenAlex

The addition of a 3' poly(A) tail is a pre-requisite for the maturation of the majority of eukaryotic transcripts. In most eukaryotic species, RNA poly(A) tails are bound by two important poly(A)-binding proteins (PABPs): PABPC1 and PABPN1 that localize to the cytoplasm and the nucleus, respectively. Such steady state localization for PABPN1 and PABPC1 led to a model whereby PABPN1-bound nuclear mRNAs are remodeled during or after nuclear export so that PABPN1 is replaced by PABPC1 to allow robust cap-dependent translation in the cytoplasm. Here we discuss evidence that challenge the view in which PABPN1 and PABPC1 function solely in the nucleus and cytoplasm, respectively. We discuss accumulating evidence that support nuclear roles for PABPC1 in mRNA biogenesis as well as cytoplasmic roles for PABPN1 in translational control. Because 3' poly(A) tails can also act as a degradation mark via the exosome complex of 3'-5' exonucleases, we also discuss recent results that involve the nuclear PABP in posttranscriptional gene regulation.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.005

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 head0.030
GPT teacher head0.314
Teacher spread0.284 · 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

Citations73
Published2010
Admission routes2
Has abstractyes

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