| Title |
DLAD4U: deriving and prioritizing disease lists from PubMed literature
|
|---|---|
| Published in |
BMC Bioinformatics, December 2018
|
| DOI | 10.1186/s12859-018-2463-0 |
| Pubmed ID | |
| Authors |
Junhui Shen, Suhas Vasaikar, Bing Zhang |
X Demographics
The data shown below were collected from the profiles of 5 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 Kingdom | 1 | 20% |
| Unknown | 4 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 80% |
| Members of the public | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 31 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 26% |
| Student > Ph. D. Student | 6 | 19% |
| Student > Master | 2 | 6% |
| Unspecified | 2 | 6% |
| Other | 1 | 3% |
| Other | 4 | 13% |
| Unknown | 8 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 19% |
| Agricultural and Biological Sciences | 4 | 13% |
| Medicine and Dentistry | 3 | 10% |
| Unspecified | 2 | 6% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Other | 6 | 19% |
| Unknown | 9 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 01 January 2019.
All research outputs
#14,149,828
of 23,120,280 outputs
Outputs from BMC Bioinformatics
#4,524
of 7,330 outputs
Outputs of similar age
#228,359
of 437,310 outputs
Outputs of similar age from BMC Bioinformatics
#124
of 213 outputs
Altmetric has tracked 23,120,280 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,330 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 35th percentile – i.e., 35% 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 437,310 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 213 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.