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X Demographics
Mendeley readers
Attention Score in Context
| Title |
DeepUbi: a deep learning framework for prediction of ubiquitination sites in proteins
|
|---|---|
| Published in |
BMC Bioinformatics, February 2019
|
| DOI | 10.1186/s12859-019-2677-9 |
| Pubmed ID | |
| Authors |
Hongli Fu, Yingxi Yang, Xiaobo Wang, Hui Wang, Yan Xu |
X Demographics
The data shown below were collected from the profiles of 18 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 39% |
| Israel | 1 | 6% |
| Sri Lanka | 1 | 6% |
| United Kingdom | 1 | 6% |
| Unknown | 8 | 44% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 67% |
| Scientists | 6 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 72 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 25% |
| Researcher | 10 | 14% |
| Student > Bachelor | 9 | 13% |
| Student > Master | 8 | 11% |
| Other | 4 | 6% |
| Other | 4 | 6% |
| Unknown | 19 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 16 | 22% |
| Computer Science | 10 | 14% |
| Agricultural and Biological Sciences | 6 | 8% |
| Medicine and Dentistry | 4 | 6% |
| Engineering | 4 | 6% |
| Other | 8 | 11% |
| Unknown | 24 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 21 May 2019.
All research outputs
#3,199,997
of 24,990,015 outputs
Outputs from BMC Bioinformatics
#1,026
of 7,629 outputs
Outputs of similar age
#68,058
of 358,610 outputs
Outputs of similar age from BMC Bioinformatics
#32
of 167 outputs
Altmetric has tracked 24,990,015 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,629 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 86% of its peers.
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 358,610 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 167 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.