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X Demographics
Mendeley readers
Attention Score in Context
| Title |
SNF-NN: computational method to predict drug-disease interactions using similarity network fusion and neural networks
|
|---|---|
| Published in |
BMC Bioinformatics, January 2021
|
| DOI | 10.1186/s12859-020-03950-3 |
| Pubmed ID | |
| Authors |
Tamer N. Jarada, Jon G. Rokne, Reda Alhajj |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 10% |
| Japan | 1 | 10% |
| United Kingdom | 1 | 10% |
| United States | 1 | 10% |
| Israel | 1 | 10% |
| Sweden | 1 | 10% |
| Unknown | 4 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 70% |
| Members of the public | 3 | 30% |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 74 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 14% |
| Student > Master | 9 | 12% |
| Student > Ph. D. Student | 8 | 11% |
| Student > Doctoral Student | 4 | 5% |
| Professor | 3 | 4% |
| Other | 10 | 14% |
| Unknown | 30 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 15 | 20% |
| Engineering | 6 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 5% |
| Agricultural and Biological Sciences | 4 | 5% |
| Biochemistry, Genetics and Molecular Biology | 4 | 5% |
| Other | 10 | 14% |
| Unknown | 31 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 05 October 2023.
All research outputs
#2,449,469
of 25,340,976 outputs
Outputs from BMC Bioinformatics
#606
of 7,676 outputs
Outputs of similar age
#65,721
of 520,703 outputs
Outputs of similar age from BMC Bioinformatics
#13
of 144 outputs
Altmetric has tracked 25,340,976 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,676 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 92% 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 520,703 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 87% of its contemporaries.
We're also able to compare this research output to 144 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 91% of its contemporaries.