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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Biological interpretation of deep neural network for phenotype prediction based on gene expression
|
|---|---|
| Published in |
BMC Bioinformatics, November 2020
|
| DOI | 10.1186/s12859-020-03836-4 |
| Pubmed ID | |
| Authors |
Blaise Hanczar, Farida Zehraoui, Tina Issa, Mathieu Arles |
X Demographics
The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 8% |
| Switzerland | 1 | 8% |
| Japan | 1 | 8% |
| India | 1 | 8% |
| Indonesia | 1 | 8% |
| United Kingdom | 1 | 8% |
| Sweden | 1 | 8% |
| Israel | 1 | 8% |
| Unknown | 5 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 54% |
| Members of the public | 6 | 46% |
Mendeley readers
The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 73 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 16% |
| Researcher | 11 | 15% |
| Student > Bachelor | 6 | 8% |
| Other | 6 | 8% |
| Student > Master | 5 | 7% |
| Other | 11 | 15% |
| Unknown | 22 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 10 | 14% |
| Agricultural and Biological Sciences | 8 | 11% |
| Computer Science | 6 | 8% |
| Nursing and Health Professions | 5 | 7% |
| Engineering | 5 | 7% |
| Other | 10 | 14% |
| Unknown | 29 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 11 November 2020.
All research outputs
#2,578,678
of 24,417,958 outputs
Outputs from BMC Bioinformatics
#735
of 7,530 outputs
Outputs of similar age
#65,432
of 425,714 outputs
Outputs of similar age from BMC Bioinformatics
#19
of 165 outputs
Altmetric has tracked 24,417,958 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,530 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 90% 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 425,714 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 165 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.