Evidence map›Paper›PMID 22126294›Full record

ReviewEpigenomics2011

DNA methylation topology: potential of a chromatin landmark for epigenetic drug toxicology.

Jian Tajbakhsh

Abstract readReview
In one paragraph

Review in Epigenomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Jian TajbakhshChromatin Biology Laboratory, Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA. tajbakhshj@cshs.org

Funding

High-Content Image Analysis of Global DNA Methylation Patterns for Drug ScreeningR21CA143618 · NCI · CEDARS-SINAI MEDICAL CENTER · PI GERTYCH, ARKADIUSZ · 2010 to 2011
$379k
NCI NIH HHS R21 CA143618
6 · The paper itself

Abstract

Targeting chromatin and its basic components through epigenetic drug therapy has become an increased focus in the treatment of complex diseases. This boost calls for the implementation of high-throughput cell-based assays that exploit the increasing knowledge about epigenetic mechanisms and their interventions for genotoxicity testing of epigenetic drugs. 3D quantitative DNA methylation imaging is a novel approach for detecting drug-induced DNA demethylation and concurrent heterochromatin decondensation/reorganization in cells through the analysis of differential nuclear distribution patterns of methylcytosine and gDNA visualized by fluorescence and processed by machine-learning algorithms. Utilizing 3D DNA methylation patterns is a powerful precursor to a series of fully automatable assays that employ chromatin structure and higher organization as novel pharmacodynamic biomarkers for various epigenetic drug actions.

Indexed as

BiomarkersChromatinCytosineDiagnostic ImagingDNA MethylationDrug DiscoveryDrug TherapyEpigenesis, GeneticHumansMutagenicity TestsBiomarkersChromatinCytosine

Identifiers

PMID22126294
PMCPMC3250213

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.