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Record W2122131968 · doi:10.1109/ccece.2000.849758

Multithreaded implementation of a biomolecular sequence alignment algorithm-software/information technology

2002· article· en· W2122131968 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
FieldComputer Science
TopicAlgorithms and Data Compression
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAlignment-free sequence analysisMultiple sequence alignmentDynamic programmingComputer scienceSequence alignmentSmith–Waterman algorithmStructural alignmentSequence (biology)Tree (set theory)AlgorithmHeuristicPairwise comparisonSoftwareArtificial intelligenceMathematicsPeptide sequenceBiology

Abstract

fetched live from OpenAlex

This paper describes a parallel implementation of a sequence alignment algorithm for biomolecular sequence analysis. It uses multiple threaded programming for the most time consuming functions and works in X Window based interactive systems. Its sequence alignment operations include pairwise alignment, star alignment, phylogeny reconstruction and generalized tree alignment. Both of fast and optimal modes are provided. The algorithms for phylogeny reconstruction, generalized tree alignment, and tree alignment are based on heuristic stepwise addition and internal node sequence alignment induction methods. PTAR can be used for DNA, RNA, and protein sequence analysis. In general, the system can carry out the alignments for any sequences composed of characters a-z and A-Z.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.988
Threshold uncertainty score0.356

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 communication0.0000.001
Open science0.0010.000
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 head0.020
GPT teacher head0.275
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

Quick stats

Citations2
Published2002
Admission routes1
Has abstractyes

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