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Record W2264932884 · doi:10.1038/srep09934

Promoter-Autonomous Functioning in a Controlled Environment using Single Molecule FISH

2015· article· en· W2264932884 on OpenAlexafffund
Sami Hocine, María Vera, Daniel Zenklusen, Robert H. Singer

Bibliographic record

VenueScientific Reports · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversité de Montréal
FundersNational Institute of General Medical SciencesCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsPromoterGeneBiologyTranscription (linguistics)ENCODELocus (genetics)GeneticsTranscription factorTranscriptional regulationComputational biologyRegulation of gene expressionGene expression

Abstract

fetched live from OpenAlex

Transcription is a highly regulated biological process, initiated through the assembly of complexes at the promoter that contain both the general transcriptional machinery and promoter-specific factors. Despite the abundance of studies focusing on transcription, certain questions have remained unanswered. It is not clear how the transcriptional profile of a promoter is affected by genomic context. Also, there is no single cell method to directly compare transcriptional profiles independent of gene length and sequence. In this work, we employ a single genetic site for isolating the transcriptional kinetics of yeast promoters. Utilizing single molecule FISH, we directly compare the transcriptional activity of different promoters, considering both synthesis and cell-to-cell variability. With this approach, we provide evidence suggesting promoters autonomously encode their associated transcriptional profiles, independent of genomic locus, gene length and gene sequence.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.255
Teacher spread0.240 · 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 designBench or experimental
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

Citations18
Published2015
Admission routes2
Has abstractyes

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