You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
RPI-SE: a stacking ensemble learning framework for ncRNA-protein interactions prediction using sequence information
|
|---|---|
| Published in |
BMC Bioinformatics, February 2020
|
| DOI | 10.1186/s12859-020-3406-0 |
| Pubmed ID | |
| Authors |
Hai-Cheng Yi, Zhu-Hong You, Mei-Neng Wang, Zhen-Hao Guo, Yan-Bin Wang, Ji-Ren Zhou |
X Demographics
The data shown below were collected from the profiles of 3 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 | 33% |
| France | 1 | 33% |
| United Kingdom | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 18% |
| Student > Bachelor | 2 | 9% |
| Student > Doctoral Student | 1 | 5% |
| Student > Master | 1 | 5% |
| Researcher | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 13 | 59% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 4 | 18% |
| Biochemistry, Genetics and Molecular Biology | 3 | 14% |
| Agricultural and Biological Sciences | 2 | 9% |
| Unknown | 13 | 59% |
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 17 April 2020.
All research outputs
#19,100,659
of 24,321,976 outputs
Outputs from BMC Bioinformatics
#6,135
of 7,513 outputs
Outputs of similar age
#258,693
of 364,789 outputs
Outputs of similar age from BMC Bioinformatics
#80
of 111 outputs
Altmetric has tracked 24,321,976 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,513 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 13th percentile – i.e., 13% 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 364,789 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 111 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.