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Mendeley readers
Attention Score in Context
| Title |
The Drosophila phenotype ontology
|
|---|---|
| Published in |
Journal of Biomedical Semantics, October 2013
|
| DOI | 10.1186/2041-1480-4-30 |
| Pubmed ID | |
| Authors |
David Osumi-Sutherland, Steven J Marygold, Gillian H Millburn, Peter A McQuilton, Laura Ponting, Raymund Stefancsik, Kathleen Falls, Nicholas H Brown, Georgios V Gkoutos |
| Abstract |
Phenotype ontologies are queryable classifications of phenotypes. They provide a widely-used means for annotating phenotypes in a form that is human-readable, programatically accessible and that can be used to group annotations in biologically meaningful ways. Accurate manual annotation requires clear textual definitions for terms. Accurate grouping and fruitful programatic usage require high-quality formal definitions that can be used to automate classification. The Drosophila phenotype ontology (DPO) has been used to annotate over 159,000 phenotypes in FlyBase to date, but until recently lacked textual or formal definitions. |
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 % |
|---|---|---|
| Canada | 1 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
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 States | 2 | 4% |
| Mexico | 1 | 2% |
| Turkey | 1 | 2% |
| Canada | 1 | 2% |
| Unknown | 44 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 31% |
| Student > Ph. D. Student | 6 | 12% |
| Student > Master | 5 | 10% |
| Professor > Associate Professor | 4 | 8% |
| Other | 4 | 8% |
| Other | 11 | 22% |
| Unknown | 4 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 21 | 43% |
| Biochemistry, Genetics and Molecular Biology | 13 | 27% |
| Computer Science | 5 | 10% |
| Engineering | 2 | 4% |
| Social Sciences | 1 | 2% |
| Other | 3 | 6% |
| Unknown | 4 | 8% |
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 04 December 2013.
All research outputs
#15,168,167
of 25,371,288 outputs
Outputs from Journal of Biomedical Semantics
#198
of 368 outputs
Outputs of similar age
#121,797
of 224,543 outputs
Outputs of similar age from Journal of Biomedical Semantics
#11
of 19 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 368 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 43rd percentile – i.e., 43% 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 224,543 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.