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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The Drosophila anatomy ontology
|
|---|---|
| Published in |
Journal of Biomedical Semantics, October 2013
|
| DOI | 10.1186/2041-1480-4-32 |
| Pubmed ID | |
| Authors |
Marta Costa, Simon Reeve, Gary Grumbling, David Osumi-Sutherland |
| Abstract |
Anatomy ontologies are query-able classifications of anatomical structures. They provide a widely-used means for standardising the annotation of phenotypes and expression in both human-readable and programmatically accessible forms. They are also frequently used to group annotations in biologically meaningful ways. Accurate annotation requires clear textual definitions for terms, ideally accompanied by images. Accurate grouping and fruitful programmatic usage requires high-quality formal definitions that can be used to automate classification and check for errors. The Drosophila anatomy ontology (DAO) consists of over 8000 classes with broad coverage of Drosophila anatomy. It has been used extensively for annotation by a range of resources, but until recently it was poorly formalised and had few textual definitions. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 2% |
| United States | 1 | 2% |
| Turkey | 1 | 2% |
| Canada | 1 | 2% |
| Unknown | 47 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 35% |
| Student > Ph. D. Student | 11 | 22% |
| Student > Master | 5 | 10% |
| Student > Doctoral Student | 3 | 6% |
| Professor > Associate Professor | 3 | 6% |
| Other | 2 | 4% |
| Unknown | 9 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 23 | 45% |
| Biochemistry, Genetics and Molecular Biology | 8 | 16% |
| Computer Science | 4 | 8% |
| Neuroscience | 4 | 8% |
| Chemistry | 2 | 4% |
| Other | 1 | 2% |
| Unknown | 9 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 10 February 2020.
All research outputs
#6,282,360
of 23,577,654 outputs
Outputs from Journal of Biomedical Semantics
#106
of 361 outputs
Outputs of similar age
#56,163
of 213,473 outputs
Outputs of similar age from Journal of Biomedical Semantics
#2
of 6 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 361 research outputs from this source. They receive a mean Attention Score of 4.6. This one has gotten more attention than average, scoring higher than 69% 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 213,473 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 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.