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Chromatin Immunoprecipitation in Mammalian Cells

2009· article· en· W145266312 on OpenAlexaff
Amy Svotelis, Nicolas Gévry, Luc Gaudreau

Bibliographic record

VenueMethods in molecular biology · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsChromatin immunoprecipitationChromatinChIA-PETChIP-on-chipChIP-sequencingBiologyCell biologyBivalent chromatinRNA polymerase IIImmunoprecipitationPromoterGeneTranscription (linguistics)Chromatin remodelingMolecular biologyGene expressionGenetics

Abstract

fetched live from OpenAlex

The ensemble of the genes in the mammalian genome is organized into a structure of DNA and proteins known as chromatin. The control of gene expression by the proteins that bind to chromatin regulates many cell processes, such as differentiation and proliferation. Transcription of protein-encoding genes in mammalian cells is performed by the concerted action of the RNA polymerase II holoenzyme, transcription factors, co-activator complexes that bind to the promoter areas of genes. In addition, different proteins can interact with these complexes and chromatin to create a repressive state. In order to fundamentally understand transcriptional control, it is important to define the areas that these proteins will bind. Classical laboratory techniques unable to provide distinct locations of these factors have now been replaced by the chromatin immunoprecipitation (ChIP) assay. The ChIP technique allows us to isolate chromatin along with its associated proteins from cells and analyse the binding sites of specific proteins and complexes at high resolution.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.292
Threshold uncertainty score0.819

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.008
GPT teacher head0.331
Teacher spread0.322 · 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 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

Citations22
Published2009
Admission routes1
Has abstractyes

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