You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
NEMPD: a network embedding-based method for predicting miRNA-disease associations by preserving behavior and attribute information
|
|---|---|
| Published in |
BMC Bioinformatics, September 2020
|
| DOI | 10.1186/s12859-020-03716-x |
| Pubmed ID | |
| Authors |
Bo-Ya Ji, Zhu-Hong You, Zhan-Heng Chen, Leon Wong, Hai-Cheng Yi |
X Demographics
The data shown below were collected from the profiles of 3 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 | 33% |
| Sweden | 1 | 33% |
| United Kingdom | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 11% |
| Researcher | 2 | 11% |
| Student > Doctoral Student | 1 | 5% |
| Other | 1 | 5% |
| Student > Postgraduate | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 12 | 63% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 4 | 21% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Neuroscience | 1 | 5% |
| Medicine and Dentistry | 1 | 5% |
| Unknown | 12 | 63% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 September 2020.
All research outputs
#15,627,783
of 23,237,082 outputs
Outputs from BMC Bioinformatics
#5,450
of 7,359 outputs
Outputs of similar age
#249,214
of 401,151 outputs
Outputs of similar age from BMC Bioinformatics
#122
of 147 outputs
Altmetric has tracked 23,237,082 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,359 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% 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 401,151 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 147 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.