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Record W2414569285 · doi:10.1007/978-1-59745-514-5_11

Organizing and Updating Whole Genome BLAST Searches with ReHAB

2007· article· en· W2414569285 on OpenAlexaff
David J. Esteban, Aijazuddin Syed, Chris Upton

Bibliographic record

VenueMethods in molecular biology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsGenomeSimilarity (geometry)Computer scienceGenomicsSequence (biology)Data miningSoftwareMultiple sequence alignmentResource (disambiguation)Sequence alignmentInformation retrievalComputational biologyBiologyArtificial intelligenceGeneticsGeneProgramming language

Abstract

fetched live from OpenAlex

In the current genomics era, protein and DNA sequence databases are continuously growing at an exponential rate. It has become increasingly important and useful to repeat similarity searches at frequent intervals, which then retrieve larger and larger sets of results. In addition, sequence similarity searches are now often performed with many sequences or even whole genomes. ReHAB (Recent Hits Acquired from Basic Local Alignment Search Tool [BLAST]) is a tool for tracking new protein hits in repeated PSI-BLAST searches. It is designed to simplify the analysis of large numbers of database matches and is therefore especially suited to comparative genomics. Results are presented in a user-friendly graphical interface with simple-to-navigate tables and new hits are indicated by highlighted text. In this paper, we describe the use of this software for organizing results from whole virus genome PSI-BLAST searches using a ReHAB database maintained at the Virus Bioinformatics Resource Centre.

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)0.008
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.022
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0050.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0160.014

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 head0.019
GPT teacher head0.340
Teacher spread0.321 · 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 designNot applicable
Domainnot available
GenreSoftware

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

Citations1
Published2007
Admission routes1
Has abstractyes

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