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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep Collaborative Filtering for Prediction of Disease Genes
|
|---|---|
| Published in |
IEEE/ACM Transactions on Computational Biology and Bioinformatics, March 2019
|
| DOI | 10.1109/tcbb.2019.2907536 |
| Pubmed ID | |
| Authors |
Xiangxiang Zeng, Yinglai Lin, Yuying He, Linyuan Lü, Xiaoping Min, Alfonso Rodríguez-Patón |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 45 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 18% |
| Student > Master | 5 | 11% |
| Researcher | 3 | 7% |
| Student > Bachelor | 2 | 4% |
| Student > Doctoral Student | 2 | 4% |
| Other | 7 | 16% |
| Unknown | 18 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 17 | 38% |
| Physics and Astronomy | 3 | 7% |
| Medicine and Dentistry | 2 | 4% |
| Agricultural and Biological Sciences | 1 | 2% |
| Nursing and Health Professions | 1 | 2% |
| Other | 4 | 9% |
| Unknown | 17 | 38% |
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 02 April 2019.
All research outputs
#17,295,853
of 25,385,509 outputs
Outputs from IEEE/ACM Transactions on Computational Biology and Bioinformatics
#493
of 1,081 outputs
Outputs of similar age
#233,810
of 364,122 outputs
Outputs of similar age from IEEE/ACM Transactions on Computational Biology and Bioinformatics
#7
of 12 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,081 research outputs from this source. They receive a mean Attention Score of 2.4. This one is in the 41st percentile – i.e., 41% 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 364,122 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.