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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A representation learning model based on variational inference and graph autoencoder for predicting lncRNA-disease associations
|
|---|---|
| Published in |
BMC Bioinformatics, March 2021
|
| DOI | 10.1186/s12859-021-04073-z |
| Pubmed ID | |
| Authors |
Zhuangwei Shi, Han Zhang, Chen Jin, Xiongwen Quan, Yanbin Yin |
X Demographics
The data shown below were collected from the profiles of 4 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 | 25% |
| Sweden | 1 | 25% |
| United Kingdom | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 37 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 14% |
| Researcher | 4 | 11% |
| Student > Bachelor | 2 | 5% |
| Lecturer | 2 | 5% |
| Student > Doctoral Student | 1 | 3% |
| Other | 4 | 11% |
| Unknown | 19 | 51% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 11 | 30% |
| Agricultural and Biological Sciences | 3 | 8% |
| Engineering | 2 | 5% |
| Mathematics | 1 | 3% |
| Medicine and Dentistry | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 18 | 49% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 March 2021.
All research outputs
#16,333,240
of 24,833,726 outputs
Outputs from BMC Bioinformatics
#5,255
of 7,594 outputs
Outputs of similar age
#253,074
of 430,415 outputs
Outputs of similar age from BMC Bioinformatics
#144
of 168 outputs
Altmetric has tracked 24,833,726 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,594 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 26th percentile – i.e., 26% 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 430,415 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 168 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.