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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Efficient link prediction in the protein–protein interaction network using topological information in a generative adversarial network machine learning model
|
|---|---|
| Published in |
BMC Bioinformatics, February 2022
|
| DOI | 10.1186/s12859-022-04598-x |
| Pubmed ID | |
| Authors |
Olivér M. Balogh, Bettina Benczik, András Horváth, Mátyás Pétervári, Péter Csermely, Péter Ferdinandy, Bence Ágg |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Argentina | 1 | 20% |
| India | 1 | 20% |
| Sweden | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Members of the public | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 41 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 17% |
| Student > Master | 4 | 10% |
| Student > Bachelor | 3 | 7% |
| Researcher | 2 | 5% |
| Other | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 21 | 51% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 12% |
| Engineering | 3 | 7% |
| Agricultural and Biological Sciences | 2 | 5% |
| Computer Science | 2 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 25 | 61% |
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 01 May 2024.
All research outputs
#15,208,947
of 25,824,818 outputs
Outputs from BMC Bioinformatics
#4,309
of 7,754 outputs
Outputs of similar age
#206,382
of 454,073 outputs
Outputs of similar age from BMC Bioinformatics
#70
of 126 outputs
Altmetric has tracked 25,824,818 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,754 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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 454,073 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 53% of its contemporaries.
We're also able to compare this research output to 126 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.