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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A big data approach to metagenomics for all-food-sequencing
|
|---|---|
| Published in |
BMC Bioinformatics, March 2020
|
| DOI | 10.1186/s12859-020-3429-6 |
| Pubmed ID | |
| Authors |
Robin Kobus, José M. Abuín, André Müller, Sören Lukas Hellmann, Juan C. Pichel, Tomás F. Pena, Andreas Hildebrandt, Thomas Hankeln, Bertil Schmidt |
X Demographics
The data shown below were collected from the profiles of 11 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 | 1 | 9% |
| India | 1 | 9% |
| Israel | 1 | 9% |
| United Kingdom | 1 | 9% |
| Spain | 1 | 9% |
| Unknown | 6 | 55% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 6 | 55% |
| Members of the public | 5 | 45% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 51 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 20% |
| Researcher | 5 | 10% |
| Student > Master | 5 | 10% |
| Student > Bachelor | 4 | 8% |
| Professor | 2 | 4% |
| Other | 7 | 14% |
| Unknown | 18 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 7 | 14% |
| Agricultural and Biological Sciences | 5 | 10% |
| Computer Science | 3 | 6% |
| Environmental Science | 3 | 6% |
| Engineering | 2 | 4% |
| Other | 10 | 20% |
| Unknown | 21 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 28 May 2020.
All research outputs
#4,541,759
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#1,683
of 7,387 outputs
Outputs of similar age
#95,219
of 365,091 outputs
Outputs of similar age from BMC Bioinformatics
#36
of 118 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,387 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 well, scoring higher than 77% 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 365,091 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 73% of its contemporaries.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.