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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A random forest based computational model for predicting novel lncRNA-disease associations
|
|---|---|
| Published in |
BMC Bioinformatics, March 2020
|
| DOI | 10.1186/s12859-020-3458-1 |
| Pubmed ID | |
| Authors |
Dengju Yao, Xiaojuan Zhan, Xiaorong Zhan, Chee Keong Kwoh, Peng Li, Jinke Wang |
X Demographics
The data shown below were collected from the profiles of 2 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 | 50% |
| United Kingdom | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 42 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 14% |
| Student > Bachelor | 5 | 12% |
| Student > Doctoral Student | 3 | 7% |
| Researcher | 3 | 7% |
| Lecturer | 2 | 5% |
| Other | 4 | 10% |
| Unknown | 19 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 21% |
| Biochemistry, Genetics and Molecular Biology | 3 | 7% |
| Agricultural and Biological Sciences | 3 | 7% |
| Engineering | 2 | 5% |
| Medicine and Dentistry | 2 | 5% |
| Other | 6 | 14% |
| Unknown | 17 | 40% |
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 28 March 2020.
All research outputs
#18,717,206
of 23,199,478 outputs
Outputs from BMC Bioinformatics
#6,384
of 7,349 outputs
Outputs of similar age
#276,022
of 368,324 outputs
Outputs of similar age from BMC Bioinformatics
#102
of 119 outputs
Altmetric has tracked 23,199,478 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,349 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% 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 368,324 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.