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Mendeley readers
Attention Score in Context
| Title |
IntelliGO: a new vector-based semantic similarity measure including annotation origin
|
|---|---|
| Published in |
BMC Bioinformatics, December 2010
|
| DOI | 10.1186/1471-2105-11-588 |
| Pubmed ID | |
| Authors |
Sidahmed Benabderrahmane, Malika Smail-Tabbone, Olivier Poch, Amedeo Napoli, Marie-Dominique Devignes |
| Abstract |
The Gene Ontology (GO) is a well known controlled vocabulary describing the biological process, molecular function and cellular component aspects of gene annotation. It has become a widely used knowledge source in bioinformatics for annotating genes and measuring their semantic similarity. These measures generally involve the GO graph structure, the information content of GO aspects, or a combination of both. However, only a few of the semantic similarity measures described so far can handle GO annotations differently according to their origin (i.e. their evidence codes). |
Mendeley readers
The data shown below were compiled from readership statistics for 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 5% |
| Brazil | 3 | 2% |
| Portugal | 2 | 2% |
| Germany | 2 | 2% |
| France | 2 | 2% |
| United Kingdom | 2 | 2% |
| Mexico | 1 | <1% |
| Unknown | 110 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 34 | 27% |
| Student > Ph. D. Student | 30 | 23% |
| Student > Master | 20 | 16% |
| Professor > Associate Professor | 9 | 7% |
| Professor | 6 | 5% |
| Other | 22 | 17% |
| Unknown | 7 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 47 | 37% |
| Agricultural and Biological Sciences | 41 | 32% |
| Biochemistry, Genetics and Molecular Biology | 11 | 9% |
| Engineering | 6 | 5% |
| Mathematics | 4 | 3% |
| Other | 11 | 9% |
| Unknown | 8 | 6% |
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 14 February 2011.
All research outputs
#7,453,126
of 22,785,242 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,279 outputs
Outputs of similar age
#54,103
of 180,482 outputs
Outputs of similar age from BMC Bioinformatics
#20
of 57 outputs
Altmetric has tracked 22,785,242 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,279 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 50% 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 180,482 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
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 is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.