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Record W2551087326 · doi:10.1139/cjm-2016-0576

The essential activities of the bacterial sigma factor

2016· review· en· W2551087326 on OpenAlexafffundvenue
Maria C. Davis, Christopher A. Kesthely, Emily A. Franklin, Shawn R. MacLellan

Bibliographic record

VenueCanadian Journal of Microbiology · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsUniversity of New Brunswick
FundersNational Institute of General Medical SciencesNatural Sciences and Engineering Research Council of CanadaUniversity of California, San Francisco
KeywordsSigma factorPromoterRNA polymeraseBiologyTranscription (linguistics)General transcription factorDNARNA polymerase IITranscription factor II ETranscription preinitiation complexRNA polymerase II holoenzymeTranscription factorTranscription factor II DGeneCell biologyGeneticsBacterial transcriptionRNAGene expression

Abstract

fetched live from OpenAlex

Transcription is the first and most heavily regulated step in gene expression. Sigma (σ) factors are general transcription factors that reversibly bind RNA polymerase (RNAP) and mediate transcription of all genes in bacteria. σ Factors play 3 major roles in the RNA synthesis initiation process: they (i) target RNAP holoenzyme to specific promoters, (ii) melt a region of double-stranded promoter DNA and stabilize it as a single-stranded open complex, and (iii) interact with other DNA-binding transcription factors to contribute complexity to gene expression regulation schemes. Recent structural studies have demonstrated that when σ factors bind promoter DNA, they capture 1 or more nucleotides that are flipped out of the helical DNA stack and this stabilizes the promoter open-complex intermediate that is required for the initiation of RNA synthesis. This review describes the structure and function of the σ 70 family of σ proteins and the essential roles they play in the transcription process.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.953
Threshold uncertainty score0.697

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations86
Published2016
Admission routes3
Has abstractyes

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