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Record W2114795070 · doi:10.1002/anie.201308584

Recoding the Genetic Code with Selenocysteine

2013· article· en· W2114795070 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.

Bibliographic record

VenueAngewandte Chemie International Edition · 2013
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsWestern University
FundersNational Institute of General Medical Sciences
KeywordsSelenocysteineGenetic codeComputational biologyCode (set theory)ChemistryProgramming languageGeneticsBiologyComputer scienceBiochemistryGene

Abstract

fetched live from OpenAlex

Selenocysteine (Sec) is naturally incorporated into proteins by recoding the stop codon UGA. Sec is not hardwired to UGA, as the Sec insertion machinery was found to be able to site-specifically incorporate Sec directed by 58 of the 64 codons. For 15 sense codons, complete conversion of the codon meaning from canonical amino acid (AA) to Sec was observed along with a tenfold increase in selenoprotein yield compared to Sec insertion at the three stop codons. This high-fidelity sense-codon recoding mechanism was demonstrated for Escherichia coli formate dehydrogenase and recombinant human thioredoxin reductase and confirmed by independent biochemical and biophysical methods. Although Sec insertion at UGA is known to compete against protein termination, it is surprising that the Sec machinery has the ability to outcompete abundant aminoacyl-tRNAs in decoding sense codons. The findings have implications for the process of translation and the information storage capacity of the biological cell.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.248
Teacher spread0.228 · 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