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X Demographics
Mendeley readers
Attention Score in Context
| Title |
CHICKN: extraction of peptide chromatographic elution profiles from large scale mass spectrometry data by means of Wasserstein compressive hierarchical cluster analysis
|
|---|---|
| Published in |
BMC Bioinformatics, February 2021
|
| DOI | 10.1186/s12859-021-03969-0 |
| Pubmed ID | |
| Authors |
Olga Permiakova, Romain Guibert, Alexandra Kraut, Thomas Fortin, Anne-Marie Hesse, Thomas Burger |
X Demographics
The data shown below were collected from the profiles of 8 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 Kingdom | 2 | 25% |
| Sweden | 1 | 13% |
| Belgium | 1 | 13% |
| Unknown | 4 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 50% |
| Scientists | 3 | 38% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 2 | 17% |
| Unspecified | 1 | 8% |
| Other | 1 | 8% |
| Professor | 1 | 8% |
| Student > Doctoral Student | 1 | 8% |
| Other | 2 | 17% |
| Unknown | 4 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 2 | 17% |
| Engineering | 2 | 17% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
| Chemical Engineering | 1 | 8% |
| Chemistry | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 4 | 33% |
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 16 February 2021.
All research outputs
#12,915,045
of 23,281,392 outputs
Outputs from BMC Bioinformatics
#3,651
of 7,370 outputs
Outputs of similar age
#219,959
of 514,764 outputs
Outputs of similar age from BMC Bioinformatics
#85
of 150 outputs
Altmetric has tracked 23,281,392 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,370 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 gotten more attention than average, scoring higher than 50% 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 514,764 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 56% of its contemporaries.
We're also able to compare this research output to 150 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.