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Record W2061320085 · doi:10.1110/ps.03148703

Archaeal signal peptides—A comparative survey at the genome level

2003· article· en· W2061320085 on OpenAlexafffund
Sonia L. Bardy, Jerry Eichler, Ken F. Jarrell

Bibliographic record

VenueProtein Science · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaIsrael Science Foundation
KeywordsSignal peptideSignal peptidaseEndoplasmic reticulumBiologySignal recognition particleGenomeProtein Sorting SignalsPeptide sequenceBiochemistryBacteriaProtein targetingAmino acidTarget peptidePeptideMembrane proteinComputational biologyArchaeaWhole genome sequencingCell biologyMembraneGeneticsGene

Abstract

fetched live from OpenAlex

The correct delivery of noncytoplasmic proteins to locations both within and outside the cell depends on the appropriate targeting signals. Protein translocation across the bacterial plasma membrane and the eukaryal endoplasmic reticulum membrane relies on cleavable N-terminal signal peptides. Although the signal peptides of secreted proteins in Bacteria and Eukarya have been extensively studied at the sequence, structure, and functional levels, little is known of the nature of archaeal signal peptides. In this report, genome-based analysis was performed in an attempt to define the amino acid composition, length, and cleavage sites of various signal peptide classes in a wide range of archaeal species. The results serve to present a picture of the archaeal signal peptide, revealing the incorporation of bacterial, eukaryal, and archaeal traits.

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)0.000
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.289
Teacher spread0.225 · 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

Citations60
Published2003
Admission routes2
Has abstractyes

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