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X Demographics
Mendeley readers
Attention Score in Context
| Title |
HPeak: an HMM-based algorithm for defining read-enriched regions in ChIP-Seq data
|
|---|---|
| Published in |
BMC Bioinformatics, July 2010
|
| DOI | 10.1186/1471-2105-11-369 |
| Pubmed ID | |
| Authors |
Zhaohui S Qin, Jianjun Yu, Jincheng Shen, Christopher A Maher, Ming Hu, Shanker Kalyana-Sundaram, Jindan Yu, Arul M Chinnaiyan |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 197 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 12 | 6% |
| United Kingdom | 5 | 3% |
| Germany | 3 | 2% |
| Italy | 2 | 1% |
| China | 2 | 1% |
| France | 2 | 1% |
| Brazil | 1 | <1% |
| Australia | 1 | <1% |
| Norway | 1 | <1% |
| Other | 4 | 2% |
| Unknown | 164 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 65 | 33% |
| Student > Ph. D. Student | 49 | 25% |
| Student > Master | 17 | 9% |
| Professor > Associate Professor | 15 | 8% |
| Student > Postgraduate | 11 | 6% |
| Other | 31 | 16% |
| Unknown | 9 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 120 | 61% |
| Biochemistry, Genetics and Molecular Biology | 23 | 12% |
| Computer Science | 14 | 7% |
| Engineering | 9 | 5% |
| Mathematics | 8 | 4% |
| Other | 9 | 5% |
| Unknown | 14 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 04 April 2016.
All research outputs
#18,445,779
of 22,854,458 outputs
Outputs from BMC Bioinformatics
#6,323
of 7,292 outputs
Outputs of similar age
#84,416
of 93,978 outputs
Outputs of similar age from BMC Bioinformatics
#57
of 65 outputs
Altmetric has tracked 22,854,458 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,292 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% 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 93,978 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.