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X Demographics
Mendeley readers
Attention Score in Context
| Title |
CHIPIN: ChIP-seq inter-sample normalization based on signal invariance across transcriptionally constant genes
|
|---|---|
| Published in |
BMC Bioinformatics, August 2021
|
| DOI | 10.1186/s12859-021-04320-3 |
| Pubmed ID | |
| Authors |
Lélia Polit, Gwenneg Kerdivel, Sebastian Gregoricchio, Michela Esposito, Christel Guillouf, Valentina Boeva |
X Demographics
The data shown below were collected from the profiles of 48 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 | 14 | 29% |
| United Kingdom | 7 | 15% |
| France | 4 | 8% |
| India | 2 | 4% |
| Germany | 1 | 2% |
| Austria | 1 | 2% |
| Czechia | 1 | 2% |
| Sweden | 1 | 2% |
| Turkey | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 16 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 31 | 65% |
| Members of the public | 16 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 21% |
| Student > Ph. D. Student | 5 | 21% |
| Student > Doctoral Student | 3 | 13% |
| Professor > Associate Professor | 2 | 8% |
| Student > Master | 2 | 8% |
| Other | 1 | 4% |
| Unknown | 6 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 10 | 42% |
| Computer Science | 2 | 8% |
| Medicine and Dentistry | 2 | 8% |
| Agricultural and Biological Sciences | 1 | 4% |
| Chemical Engineering | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 7 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 24. 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 30 October 2021.
All research outputs
#1,608,690
of 25,385,509 outputs
Outputs from BMC Bioinformatics
#252
of 7,692 outputs
Outputs of similar age
#38,088
of 436,639 outputs
Outputs of similar age from BMC Bioinformatics
#5
of 114 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,692 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 96% 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 436,639 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 91% of its contemporaries.
We're also able to compare this research output to 114 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.