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X Demographics
Mendeley readers
Attention Score in Context
| Title |
DNA Ligase-Based Strategy for Quantifying Heterogeneous DNA Methylation without Sequencing
|
|---|---|
| Published in |
Clinical Chemistry, January 2015
|
| DOI | 10.1373/clinchem.2014.227546 |
| Pubmed ID | |
| Authors |
Eugene J H Wee, Sakandar Rauf, Muhammad J A Shiddiky, Alexander Dobrovic, Matt Trau |
| Abstract |
DNA methylation is a potential source of disease biomarkers. Typically, methylation levels are measured at individual cytosine/guanine (CpG) sites or over a short region of interest. However, regions of interest often show heterogeneous methylation comprising multiple patterns of methylation (epialleles) on individual DNA strands. Heterogeneous methylation is largely ignored because digital methods are required to deconvolute these usually complex patterns of epialleles. Currently, only single-molecule approaches, such as next generation sequencing (NGS), can provide detailed epiallele information. Because NGS is not yet feasible for routine practice, we developed a single-molecule-like approach, named for epiallele quantification (EpiQ). |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 33% |
| India | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 21% |
| Researcher | 3 | 16% |
| Student > Bachelor | 2 | 11% |
| Other | 2 | 11% |
| Student > Master | 2 | 11% |
| Other | 1 | 5% |
| Unknown | 5 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 26% |
| Biochemistry, Genetics and Molecular Biology | 4 | 21% |
| Chemistry | 2 | 11% |
| Medicine and Dentistry | 1 | 5% |
| Environmental Science | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 6 | 32% |
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 07 March 2019.
All research outputs
#6,780,483
of 22,765,347 outputs
Outputs from Clinical Chemistry
#2,420
of 7,372 outputs
Outputs of similar age
#92,789
of 352,895 outputs
Outputs of similar age from Clinical Chemistry
#27
of 68 outputs
Altmetric has tracked 22,765,347 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 7,372 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has gotten more attention than average, scoring higher than 66% 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 352,895 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 73% of its contemporaries.
We're also able to compare this research output to 68 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 58% of its contemporaries.