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Mendeley readers
Attention Score in Context
| Title |
An optimized algorithm for detecting and annotating regional differential methylation
|
|---|---|
| Published in |
BMC Bioinformatics, April 2013
|
| DOI | 10.1186/1471-2105-14-s5-s10 |
| Pubmed ID | |
| Authors |
Sheng Li, Francine E Garrett-Bakelman, Altuna Akalin, Paul Zumbo, Ross Levine, Bik L To, Ian D Lewis, Anna L Brown, Richard J D'Andrea, Ari Melnick, Christopher E Mason |
| Abstract |
DNA methylation profiling reveals important differentially methylated regions (DMRs) of the genome that are altered during development or that are perturbed by disease. To date, few programs exist for regional analysis of enriched or whole-genome bisulfate conversion sequencing data, even though such data are increasingly common. Here, we describe an open-source, optimized method for determining empirically based DMRs (eDMR) from high-throughput sequence data that is applicable to enriched whole-genome methylation profiling datasets, as well as other globally enriched epigenetic modification data. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 33% |
| United Kingdom | 1 | 17% |
| Switzerland | 1 | 17% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 160 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 10 | 6% |
| Germany | 2 | 1% |
| India | 1 | <1% |
| Sweden | 1 | <1% |
| Japan | 1 | <1% |
| Russia | 1 | <1% |
| Unknown | 144 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 45 | 28% |
| Student > Ph. D. Student | 41 | 26% |
| Student > Master | 13 | 8% |
| Professor > Associate Professor | 11 | 7% |
| Student > Bachelor | 8 | 5% |
| Other | 27 | 17% |
| Unknown | 15 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 70 | 44% |
| Biochemistry, Genetics and Molecular Biology | 29 | 18% |
| Computer Science | 13 | 8% |
| Medicine and Dentistry | 8 | 5% |
| Engineering | 5 | 3% |
| Other | 16 | 10% |
| Unknown | 19 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 11 June 2020.
All research outputs
#4,581,306
of 22,708,120 outputs
Outputs from BMC Bioinformatics
#1,760
of 7,256 outputs
Outputs of similar age
#39,639
of 199,476 outputs
Outputs of similar age from BMC Bioinformatics
#32
of 135 outputs
Altmetric has tracked 22,708,120 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,256 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 75% 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 199,476 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 135 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.