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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Practical Guidelines for the Comprehensive Analysis of ChIP-seq Data
|
|---|---|
| Published in |
PLoS Computational Biology, November 2013
|
| DOI | 10.1371/journal.pcbi.1003326 |
| Pubmed ID | |
| Authors |
Timothy Bailey, Pawel Krajewski, Istvan Ladunga, Celine Lefebvre, Qunhua Li, Tao Liu, Pedro Madrigal, Cenny Taslim, Jie Zhang |
X Demographics
The data shown below were collected from the profiles of 45 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 | 9 | 20% |
| Canada | 5 | 11% |
| United Kingdom | 4 | 9% |
| Australia | 2 | 4% |
| Germany | 2 | 4% |
| France | 1 | 2% |
| Norway | 1 | 2% |
| India | 1 | 2% |
| Mexico | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 17 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 28 | 62% |
| Members of the public | 16 | 36% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 1,587 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 28 | 2% |
| United Kingdom | 13 | <1% |
| Germany | 8 | <1% |
| France | 7 | <1% |
| Spain | 5 | <1% |
| Italy | 5 | <1% |
| Brazil | 4 | <1% |
| Sweden | 4 | <1% |
| Netherlands | 4 | <1% |
| Other | 28 | 2% |
| Unknown | 1481 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 459 | 29% |
| Researcher | 398 | 25% |
| Student > Master | 195 | 12% |
| Student > Bachelor | 117 | 7% |
| Student > Doctoral Student | 64 | 4% |
| Other | 214 | 13% |
| Unknown | 140 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 732 | 46% |
| Biochemistry, Genetics and Molecular Biology | 416 | 26% |
| Computer Science | 86 | 5% |
| Medicine and Dentistry | 56 | 4% |
| Immunology and Microbiology | 29 | 2% |
| Other | 100 | 6% |
| Unknown | 168 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 29. 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 06 September 2023.
All research outputs
#1,354,758
of 25,837,817 outputs
Outputs from PLoS Computational Biology
#1,116
of 9,035 outputs
Outputs of similar age
#12,000
of 225,844 outputs
Outputs of similar age from PLoS Computational Biology
#16
of 146 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,035 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done well, scoring higher than 87% 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 225,844 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 94% of its contemporaries.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.