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X Demographics
Mendeley readers
Attention Score in Context
| Title |
GSAMDA: a computational model for predicting potential microbe–drug associations based on graph attention network and sparse autoencoder
|
|---|---|
| Published in |
BMC Bioinformatics, November 2022
|
| DOI | 10.1186/s12859-022-05053-7 |
| Pubmed ID | |
| Authors |
Yaqin Tan, Juan Zou, Linai Kuang, Xiangyi Wang, Bin Zeng, Zhen Zhang, Lei Wang |
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 % |
|---|---|---|
| India | 1 | 20% |
| Sweden | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 2 | 40% |
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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 7 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 29% |
| Unspecified | 1 | 14% |
| Student > Bachelor | 1 | 14% |
| Student > Master | 1 | 14% |
| Unknown | 2 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 2 | 29% |
| Unspecified | 1 | 14% |
| Agricultural and Biological Sciences | 1 | 14% |
| Medicine and Dentistry | 1 | 14% |
| Unknown | 2 | 29% |
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 20 November 2022.
All research outputs
#15,379,405
of 24,843,842 outputs
Outputs from BMC Bioinformatics
#4,683
of 7,595 outputs
Outputs of similar age
#221,926
of 481,030 outputs
Outputs of similar age from BMC Bioinformatics
#84
of 156 outputs
Altmetric has tracked 24,843,842 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,595 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 35th percentile – i.e., 35% 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 481,030 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 52% of its contemporaries.
We're also able to compare this research output to 156 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.