| Title |
S3DB core: a framework for RDF generation and management in bioinformatics infrastructures
|
|---|---|
| Published in |
BMC Bioinformatics, July 2010
|
| DOI | 10.1186/1471-2105-11-387 |
| Pubmed ID | |
| Authors |
Jonas S Almeida, Helena F Deus, Wolfgang Maass |
| Abstract |
Biomedical research is set to greatly benefit from the use of semantic web technologies in the design of computational infrastructure. However, beyond well defined research initiatives, substantial issues of data heterogeneity, source distribution, and privacy currently stand in the way towards the personalization of Medicine. |
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 % |
|---|---|---|
| United States | 1 | 33% |
| Comoros | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 11% |
| Portugal | 1 | 2% |
| Germany | 1 | 2% |
| Australia | 1 | 2% |
| Brazil | 1 | 2% |
| Sweden | 1 | 2% |
| France | 1 | 2% |
| Canada | 1 | 2% |
| United Kingdom | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 39 | 71% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 25% |
| Other | 11 | 20% |
| Student > Ph. D. Student | 11 | 20% |
| Professor > Associate Professor | 5 | 9% |
| Student > Master | 4 | 7% |
| Other | 8 | 15% |
| Unknown | 2 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 29 | 53% |
| Computer Science | 12 | 22% |
| Medicine and Dentistry | 3 | 5% |
| Engineering | 3 | 5% |
| Social Sciences | 3 | 5% |
| Other | 3 | 5% |
| Unknown | 2 | 4% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 08 February 2014.
All research outputs
#4,666,159
of 22,660,862 outputs
Outputs from BMC Bioinformatics
#1,805
of 7,240 outputs
Outputs of similar age
#19,534
of 94,413 outputs
Outputs of similar age from BMC Bioinformatics
#13
of 57 outputs
Altmetric has tracked 22,660,862 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,240 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 73% 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 94,413 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 57 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.