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Record W7056929837

Heterogeneity and Intrinsic Variation in Spatial Genome Organization [preprint]

2017· article· en· W7056929837 on OpenAlexfundno aff

Bibliographic record

VenueThe Journal of the American Medical Association (JAMA) Network (American Medical Association) · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersNational Cancer InstituteNatural Sciences and Engineering Research Council of CanadaCommon FundNational Institutes of Health
KeywordsGenomeChromatinGenomic organizationPopulationHuman genomeStructural variationSpatial organizationGenomics
DOInot available

Abstract

fetched live from OpenAlex

The genome is hierarchically organized in 3D space and its architecture is altered in differentiation, development and disease. Some of the general principles that determine global 3D genome organization have been established. However, the extent and nature of cell-to-cell and cell-intrinsic variability in genome architecture are poorly characterized. Here, we systematically probe the heterogeneity in genome organization in human fibroblasts by combining high-resolution Hi-C datasets and high-throughput genome imaging. Optical mapping of several hundred genome interaction pairs at the single cell level demonstrates low steady-state frequencies of colocalization in the population and independent behavior of individual alleles in single nuclei. Association frequencies are determined by genomic distance, higher-order chromatin architecture and chromatin environment. These observations reveal extensive variability and heterogeneity in genome organization at the level of single cells and alleles and they demonstrate the coexistence of a broad spectrum of chromatin and genome conformations in a cell population.

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)0.013
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0100.000

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 head0.005
GPT teacher head0.250
Teacher spread0.245 · 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.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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