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Mendeley readers
Attention Score in Context
| Title |
The Autoimmune Disease Database: a dynamically compiled literature-derived database
|
|---|---|
| Published in |
BMC Bioinformatics, June 2006
|
| DOI | 10.1186/1471-2105-7-325 |
| Pubmed ID | |
| Authors |
Thomas Karopka, Juliane Fluck, Heinz-Theodor Mevissen, Änne Glass |
| Abstract |
Autoimmune diseases are disorders caused by an immune response directed against the body's own organs, tissues and cells. In practice more than 80 clinically distinct diseases, among them systemic lupus erythematosus and rheumatoid arthritis, are classified as autoimmune diseases. Although their etiology is unclear these diseases share certain similarities at the molecular level i.e. susceptibility regions on the chromosomes or the involvement of common genes. To gain an overview of these related diseases it is not feasible to do a literary review but it requires methods of automated analyses of the more than 500,000 Medline documents related to autoimmune disorders. |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 6% |
| United States | 2 | 4% |
| Russia | 1 | 2% |
| Germany | 1 | 2% |
| Unknown | 42 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 31% |
| Student > Ph. D. Student | 8 | 16% |
| Student > Master | 6 | 12% |
| Student > Doctoral Student | 4 | 8% |
| Other | 3 | 6% |
| Other | 6 | 12% |
| Unknown | 7 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 15 | 31% |
| Medicine and Dentistry | 6 | 12% |
| Biochemistry, Genetics and Molecular Biology | 6 | 12% |
| Computer Science | 5 | 10% |
| Mathematics | 2 | 4% |
| Other | 7 | 14% |
| Unknown | 8 | 16% |
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 23 August 2013.
All research outputs
#20,198,525
of 22,716,996 outputs
Outputs from BMC Bioinformatics
#6,832
of 7,260 outputs
Outputs of similar age
#62,046
of 64,195 outputs
Outputs of similar age from BMC Bioinformatics
#38
of 38 outputs
Altmetric has tracked 22,716,996 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,260 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 1st percentile – i.e., 1% 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 64,195 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.