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Profiling genome-wide DNA methylation

Overview of attention for article published in Epigenetics & Chromatin, June 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#35 of 618)
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

news
1 news outlet
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10 X users
patent
1 patent
wikipedia
1 Wikipedia page

Citations

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287 Dimensions

Readers on

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850 Mendeley
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Title
Profiling genome-wide DNA methylation
Published in
Epigenetics & Chromatin, June 2016
DOI 10.1186/s13072-016-0075-3
Pubmed ID
Authors

Wai-Shin Yong, Fei-Man Hsu, Pao-Yang Chen

Abstract

DNA methylation is an epigenetic modification that plays an important role in regulating gene expression and therefore a broad range of biological processes and diseases. DNA methylation is tissue-specific, dynamic, sequence-context-dependent and trans-generationally heritable, and these complex patterns of methylation highlight the significance of profiling DNA methylation to answer biological questions. In this review, we surveyed major methylation assays, along with comparisons and biological examples, to provide an overview of DNA methylation profiling techniques. The advances in microarray and sequencing technologies make genome-wide profiling possible at a single-nucleotide or even a single-cell resolution. These profiling approaches vary in many aspects, such as DNA input, resolution, genomic region coverage, and bioinformatics analysis, and selecting a feasible method requires knowledge of these methods. We first introduce the biological background of DNA methylation and its pattern in plants, animals and fungi. We present an overview of major experimental approaches to profiling genome-wide DNA methylation and hydroxymethylation and then extend to the single-cell methylome. To evaluate these methods, we outline their strengths and weaknesses and perform comparisons across the different platforms. Due to the increasing need to compute high-throughput epigenomic data, we interrogate the computational pipeline for bisulfite sequencing data and also discuss the concept of identifying differentially methylated regions (DMRs). This review summarizes the experimental and computational concepts for profiling genome-wide DNA methylation, followed by biological examples. Overall, this review provides researchers useful guidance for the selection of a profiling method suited to specific research questions.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 850 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 <1%
Brazil 1 <1%
Switzerland 1 <1%
United Kingdom 1 <1%
Finland 1 <1%
Unknown 843 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 179 21%
Researcher 124 15%
Student > Master 110 13%
Student > Bachelor 96 11%
Student > Postgraduate 48 6%
Other 97 11%
Unknown 196 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 282 33%
Agricultural and Biological Sciences 196 23%
Medicine and Dentistry 35 4%
Computer Science 20 2%
Neuroscience 15 2%
Other 86 10%
Unknown 216 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 15 September 2023.
All research outputs
#1,728,021
of 26,017,215 outputs
Outputs from Epigenetics & Chromatin
#35
of 618 outputs
Outputs of similar age
#30,873
of 373,370 outputs
Outputs of similar age from Epigenetics & Chromatin
#3
of 16 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 618 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done particularly well, scoring higher than 94% 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 373,370 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.