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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Structure-aware protein solubility prediction from sequence through graph convolutional network and predicted contact map
|
|---|---|
| Published in |
Journal of Cheminformatics, February 2021
|
| DOI | 10.1186/s13321-021-00488-1 |
| Pubmed ID | |
| Authors |
Jianwen Chen, Shuangjia Zheng, Huiying Zhao, Yuedong Yang |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 14% |
| Australia | 1 | 14% |
| United States | 1 | 14% |
| India | 1 | 14% |
| Unknown | 3 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Scientists | 2 | 29% |
| Science communicators (journalists, bloggers, editors) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 142 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 142 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 25 | 18% |
| Researcher | 20 | 14% |
| Student > Master | 19 | 13% |
| Other | 8 | 6% |
| Student > Bachelor | 6 | 4% |
| Other | 16 | 11% |
| Unknown | 48 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 29 | 20% |
| Agricultural and Biological Sciences | 16 | 11% |
| Computer Science | 15 | 11% |
| Chemistry | 10 | 7% |
| Medicine and Dentistry | 4 | 3% |
| Other | 18 | 13% |
| Unknown | 50 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 April 2021.
All research outputs
#5,793,118
of 23,278,709 outputs
Outputs from Journal of Cheminformatics
#484
of 862 outputs
Outputs of similar age
#144,172
of 509,267 outputs
Outputs of similar age from Journal of Cheminformatics
#15
of 28 outputs
Altmetric has tracked 23,278,709 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 862 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one is in the 43rd percentile – i.e., 43% 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 509,267 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 71% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.