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Record W2510792904 · doi:10.2217/epi-2016-0052

DNA Methylome Analysis of Acute Lymphoblastic Leukemia Cells Reveals Stochastic <i>de novo</i> DNA methylation in CpG islands

2016· article· en· W2510792904 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEpigenomics · 2016
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineMcGill University and Génome Québec Innovation Centre
FundersBarncancerfondenScience for Life LaboratoryCancerfonden
KeywordsBiologyDNA methylationCpG siteLymphoblastic LeukemiaDNAMethylationGeneticsCancer researchComputational biologyMolecular biologyLeukemiaGeneGene expression

Abstract

fetched live from OpenAlex

AIM: To identify regions of aberrant DNA methylation in acute lymphoblastic leukemia (ALL) cells of different subtypes on a genome-wide scale. MATERIALS & METHODS: Whole-genome bisulfite sequencing (WGBS) was used to determine the DNA methylation levels in cells from four pediatric ALL patients of different subtypes. The findings were confirmed by 450k DNA methylation arrays in a large patient set. RESULTS: Compared with mature B or T cells WGBS detected on average 82,000 differentially methylated regions per patient. Differentially methylated regions are enriched to CpG poor regions, active enhancers and transcriptional start sites. We also identified approximately 8000 CpG islands with variable intermediate DNA methylation that seems to occur as a result of stochastic de novo methylation. CONCLUSION: WGBS provides an unbiased view and novel insights into the DNA methylome of ALL cells.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.287
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
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 head0.014
GPT teacher head0.279
Teacher spread0.265 · 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