MétaCan
Menu
← Back to cohort
Record W2038149325 · doi:10.1145/2382936.2383035

A comparative study of codon adaptation in ssDNA and dsDNA phages

2012· article· en· W2038149325 on OpenAlexafffund
Shivapriya Chithambaram, Ramanandan Prabhakaran, Xuhua Xia

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCodon usage biasDNABiologyGenomeGeneticsAdaptation (eye)MutationGene

Abstract

fetched live from OpenAlex

Selection and mutation are the main forces that shape the codon usage patterns of viruses. Bacteriophages, just like all other viruses depend on their host's translational machinery for replication. The rate of spontaneous C→T mutations is about 100-fold higher in single stranded DNA (ssDNA) than in double stranded DNA (dsDNA). We investigated the synonymous codon usage patterns of ssDNA phages and dsDNA phages to check if the two kinds of phages exhibit any difference in codon usage adaptation. We carried out relative synonymous codon usage (RSCU) analysis of 462 dsDNA phage and 41 ssDNA phage genomes with their respective bacterial hosts. Correlation in RSCU is significantly higher between dsDNA phages and their hosts than that between ssDNA phages and their hosts (p<0.005). Among the dsDNA phages we also found significant differences in codon adaptation between the three major phage families (p<0.0001).

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.293
Teacher spread0.255 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2012
Admission routes2
Has abstractyes

Explore more

Same topicRNA and protein synthesis mechanisms→French-language works237,207→