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Record W2544775897 · doi:10.1109/mmse.2004.63

Prediction of Protein Coding Regions in DNA Sequences Using Fourier Spectral Characteristics

2005· article· en· W2544775897 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

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFractal and DNA sequence analysis
Canadian institutionsYork University
Fundersnot available
KeywordsCoding (social sciences)Fourier transformAlgorithmDNADiscrete Fourier transform (general)Computer scienceDNA sequencingCoding regionComputational biologyMathematicsShort-time Fourier transformBiologyGeneticsFourier analysisGeneStatistics

Abstract

fetched live from OpenAlex

Existing discrete Fourier transform (DFT)-based algorithms for identifying protein coding regions in DNA sequences (S. Tiwari et al., 1997, D. Anastassiou, 2001, D. Kotlar et al., 2003) exploit the empirical observation that the spectrum of protein coding regions of length N nucleotides has a peak at frequency k=N/3. In this paper, we prove the aforementioned and several other empirical observations attributed to DNA sequences. Our analytical results lead to faster and more accurate DFT-based algorithms for predicting coding regions.

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 categoriesnone
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 score0.010
Threshold uncertainty score0.269

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)0.0000.000

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 head0.027
GPT teacher head0.250
Teacher spread0.223 · 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

Quick stats

Citations26
Published2005
Admission routes1
Has abstractyes

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