You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
MeDEStrand: an improved method to infer genome-wide absolute methylation levels from DNA enrichment data
|
|---|---|
| Published in |
BMC Bioinformatics, December 2018
|
| DOI | 10.1186/s12859-018-2574-7 |
| Pubmed ID | |
| Authors |
Jingting Xu, Shimeng Liu, Ping Yin, Serdar Bulun, Yang Dai |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 80% |
| Members of the public | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 32% |
| Student > Bachelor | 4 | 18% |
| Student > Ph. D. Student | 4 | 18% |
| Professor > Associate Professor | 2 | 9% |
| Student > Master | 2 | 9% |
| Other | 1 | 5% |
| Unknown | 2 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 27% |
| Agricultural and Biological Sciences | 5 | 23% |
| Computer Science | 2 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
| Unspecified | 1 | 5% |
| Other | 4 | 18% |
| Unknown | 3 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 31 December 2018.
All research outputs
#14,095,539
of 24,093,053 outputs
Outputs from BMC Bioinformatics
#4,109
of 7,500 outputs
Outputs of similar age
#216,488
of 443,773 outputs
Outputs of similar age from BMC Bioinformatics
#107
of 206 outputs
Altmetric has tracked 24,093,053 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,500 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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 443,773 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 50% of its contemporaries.
We're also able to compare this research output to 206 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.