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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Caipirini: using gene sets to rank literature
|
|---|---|
| Published in |
BioData Mining, February 2012
|
| DOI | 10.1186/1756-0381-5-1 |
| Pubmed ID | |
| Authors |
Theodoros G Soldatos, Seán I O'Donoghue, Venkata P Satagopam, Adriano Barbosa-Silva, Georgios A Pavlopoulos, Ana Carolina Wanderley-Nogueira, Nina Mota Soares-Cavalcanti, Reinhard Schneider |
| Abstract |
Keeping up-to-date with bioscience literature is becoming increasingly challenging. Several recent methods help meet this challenge by allowing literature search to be launched based on lists of abstracts that the user judges to be 'interesting'. Some methods go further by allowing the user to provide a second input set of 'uninteresting' abstracts; these two input sets are then used to search and rank literature by relevance. In this work we present the service 'Caipirini' (http://caipirini.org) that also allows two input sets, but takes the novel approach of allowing ranking of literature based on one or more sets of genes. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 2 | 50% |
| Canada | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Luxembourg | 2 | 6% |
| Germany | 1 | 3% |
| Australia | 1 | 3% |
| Cuba | 1 | 3% |
| United States | 1 | 3% |
| Mexico | 1 | 3% |
| Unknown | 25 | 78% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 38% |
| Professor | 4 | 13% |
| Student > Ph. D. Student | 4 | 13% |
| Professor > Associate Professor | 4 | 13% |
| Other | 3 | 9% |
| Other | 4 | 13% |
| Unknown | 1 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 12 | 38% |
| Computer Science | 6 | 19% |
| Medicine and Dentistry | 4 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 6% |
| Engineering | 2 | 6% |
| Other | 1 | 3% |
| Unknown | 5 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 30 May 2012.
All research outputs
#13,012,758
of 22,662,201 outputs
Outputs from BioData Mining
#177
of 307 outputs
Outputs of similar age
#143,858
of 247,240 outputs
Outputs of similar age from BioData Mining
#1
of 1 outputs
Altmetric has tracked 22,662,201 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 307 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 41st percentile – i.e., 41% 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 247,240 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them