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Record W2124935821 · doi:10.1093/bioinformatics/bth413

EC_oligos: automated and whole-genome primer design for exons within one or between two genomes

2004· article· en· W2124935821 on OpenAlexafffund
Shaolin Liu, Nicholas A. Tinker, Stephen J. Molnar, Diane E. Mather

Bibliographic record

VenueBioinformatics · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsAgriculture and Agri-Food CanadaMcGill UniversitySte. Anne's Hospital
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsExecutableOligonucleotideGenomePrimer (cosmetics)Computational biologyExonBiologyFile Transfer ProtocolGeneticsComputer scienceSequence (biology)DNAProgramming languageGeneWorld Wide Web

Abstract

fetched live from OpenAlex

SUMMARY: EC_oligos designs oligonucleotides (oligos) from exons of annotated genomic sequence information. It can automatically and rapidly select oligos that are conserved between two sets of sequence data, and can pair up oligos for use as PCR primers. It can do this on a whole-genome scale and according to user-defined criteria. AVAILABILITY: The source code, executable program and user manual are available at ftp://ftp.ebi.ac.uk/pub/software/dos/EC_oligos/.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0490.032

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 head0.041
GPT teacher head0.272
Teacher spread0.231 · 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 designSimulation or modeling
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

Citations5
Published2004
Admission routes2
Has abstractyes

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