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 |
Predicting MiRNA-disease associations by multiple meta-paths fusion graph embedding model
|
|---|---|
| Published in |
BMC Bioinformatics, October 2020
|
| DOI | 10.1186/s12859-020-03765-2 |
| Pubmed ID | |
| Authors |
Lei Zhang, Bailong Liu, Zhengwei Li, Xiaoyan Zhu, Zhizhen Liang, Jiyong An |
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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 2 | 12% |
| Lecturer | 1 | 6% |
| Student > Ph. D. Student | 1 | 6% |
| Unspecified | 1 | 6% |
| Student > Doctoral Student | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 10 | 59% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 18% |
| Biochemistry, Genetics and Molecular Biology | 2 | 12% |
| Unspecified | 1 | 6% |
| Engineering | 1 | 6% |
| Unknown | 10 | 59% |
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 23 October 2020.
All research outputs
#14,717,488
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#4,823
of 7,418 outputs
Outputs of similar age
#231,012
of 421,186 outputs
Outputs of similar age from BMC Bioinformatics
#112
of 176 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,418 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 30th percentile – i.e., 30% 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 421,186 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 176 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.