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Record W4365135309 · doi:10.1002/wrna.1789

Physiological and engineered <scp>tRNA</scp> aminoacylation

2023· review· en· W4365135309 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

VenueWiley Interdisciplinary Reviews - RNA · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsAminoacylationGenetic codeTransfer RNAAminoacyl tRNA synthetaseRNAProtein biosynthesisTranslation (biology)BiologyNucleic acidContext (archaeology)Computational biologyAmino Acyl-tRNA SynthetasesAmino acidBiochemistryMessenger RNAGene

Abstract

fetched live from OpenAlex

Aminoacyl-tRNA synthetases form the protein family that controls the interpretation of the genetic code, with tRNA aminoacylation being the key chemical step during which an amino acid is assigned to a corresponding sequence of nucleic acids. In consequence, aminoacyl-tRNA synthetases have been studied in their physiological context, in disease states, and as tools for synthetic biology to enable the expansion of the genetic code. Here, we review the fundamentals of aminoacyl-tRNA synthetase biology and classification, with a focus on mammalian cytoplasmic enzymes. We compile evidence that the localization of aminoacyl-tRNA synthetases can be critical in health and disease. In addition, we discuss evidence from synthetic biology which made use of the importance of subcellular localization for efficient manipulation of the protein synthesis machinery. This article is categorized under: RNA Processing Translation > Translation Regulation RNA Processing > tRNA Processing RNA Export and Localization > RNA Localization.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.074
GPT teacher head0.348
Teacher spread0.274 · 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