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Record W2483125046 · doi:10.1139/bcb-2016-0085

A decade of understanding spatio-temporal regulation of DNA repair by the nuclear architecture

2016· review· en· W2483125046 on OpenAlexaffvenue
Hicham Saad, Jennifer A. Cobb

Bibliographic record

VenueBiochemistry and Cell Biology · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNucleoplasmBiologyEuchromatinDNA repairHeterochromatinMulticellular organismGenomeGeneticsNuclear poreNuclear laminaGeneCell biologyChromosomeEvolutionary biologyNuclear proteinNucleolusTranscription factorCytoplasm

Abstract

fetched live from OpenAlex

The nucleus is a hub for gene expression and is a highly organized entity. The nucleoplasm is heterogeneous, owing to the preferential localization of specific metabolic factors, which lead to the definition of nuclear compartments or bodies. The genome is organized into chromosome territories, as well as heterochromatin and euchromatin domains. Recent observations have indicated that nuclear organization is important for maintaining genomic stability. For example, nuclear organization has been implicated in stabilizing damaged DNA, repair-pathway choice, and in preventing chromosomal rearrangements. Over the past decade, several studies have revealed that dynamic changes in the nuclear architecture are important during double-strand break repair. Stemming from work in yeast, relocation of a damaged site prior to repair appears to be at least partially conserved in multicellular eukaryotes. In this review, we will discuss genome and nucleoplasm architecture, particularly the importance of the nuclear periphery in genome stability. We will also discuss how the site of relocation regulates repair-pathway choice.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.014
GPT teacher head0.241
Teacher spread0.228 · 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
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

Citations3
Published2016
Admission routes2
Has abstractyes

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