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Genome-wide epigenomic profiling for biomarker discovery

Overview of attention for article published in Clinical Epigenetics, November 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

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2 X users
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249 Mendeley
Title
Genome-wide epigenomic profiling for biomarker discovery
Published in
Clinical Epigenetics, November 2016
DOI 10.1186/s13148-016-0284-4
Pubmed ID
Authors

René A. M. Dirks, Hendrik G. Stunnenberg, Hendrik Marks

Abstract

A myriad of diseases is caused or characterized by alteration of epigenetic patterns, including changes in DNA methylation, post-translational histone modifications, or chromatin structure. These changes of the epigenome represent a highly interesting layer of information for disease stratification and for personalized medicine. Traditionally, epigenomic profiling required large amounts of cells, which are rarely available with clinical samples. Also, the cellular heterogeneity complicates analysis when profiling clinical samples for unbiased genome-wide biomarker discovery. Recent years saw great progress in miniaturization of genome-wide epigenomic profiling, enabling large-scale epigenetic biomarker screens for disease diagnosis, prognosis, and stratification on patient-derived samples. All main genome-wide profiling technologies have now been scaled down and/or are compatible with single-cell readout, including: (i) Bisulfite sequencing to determine DNA methylation at base-pair resolution, (ii) ChIP-Seq to identify protein binding sites on the genome, (iii) DNaseI-Seq/ATAC-Seq to profile open chromatin, and (iv) 4C-Seq and HiC-Seq to determine the spatial organization of chromosomes. In this review we provide an overview of current genome-wide epigenomic profiling technologies and main technological advances that allowed miniaturization of these assays down to single-cell level. For each of these technologies we evaluate their application for future biomarker discovery. We will focus on (i) compatibility of these technologies with methods used for clinical sample preservation, including methods used by biobanks that store large numbers of patient samples, and (ii) automation of these technologies for robust sample preparation and increased throughput.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 249 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 <1%
United States 1 <1%
Germany 1 <1%
Luxembourg 1 <1%
Unknown 245 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 46 18%
Researcher 42 17%
Student > Bachelor 25 10%
Student > Master 20 8%
Student > Doctoral Student 17 7%
Other 38 15%
Unknown 61 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 75 30%
Agricultural and Biological Sciences 43 17%
Medicine and Dentistry 19 8%
Computer Science 8 3%
Pharmacology, Toxicology and Pharmaceutical Science 7 3%
Other 29 12%
Unknown 68 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 April 2020.
All research outputs
#6,822,151
of 22,903,988 outputs
Outputs from Clinical Epigenetics
#464
of 1,260 outputs
Outputs of similar age
#123,352
of 414,929 outputs
Outputs of similar age from Clinical Epigenetics
#6
of 22 outputs
Altmetric has tracked 22,903,988 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,260 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has gotten more attention than average, scoring higher than 61% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 414,929 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.