Title |
Uberon, an integrative multi-species anatomy ontology
|
---|---|
Published in |
Genome Biology, January 2012
|
DOI | 10.1186/gb-2012-13-1-r5 |
Pubmed ID | |
Authors |
Christopher J Mungall, Carlo Torniai, Georgios V Gkoutos, Suzanna E Lewis, Melissa A Haendel |
Abstract |
We present Uberon, an integrated cross-species ontology consisting of over 6,500 classes representing a variety of anatomical entities, organized according to traditional anatomical classification criteria. The ontology represents structures in a species-neutral way and includes extensive associations to existing species-centric anatomical ontologies, allowing integration of model organism and human data. Uberon provides a necessary bridge between anatomical structures in different taxa for cross-species inference. It uses novel methods for representing taxonomic variation, and has proved to be essential for translational phenotype analyses. Uberon is available at http://uberon.org. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 27% |
Switzerland | 1 | 9% |
Germany | 1 | 9% |
Sweden | 1 | 9% |
United Kingdom | 1 | 9% |
Unknown | 4 | 36% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 6 | 55% |
Scientists | 3 | 27% |
Practitioners (doctors, other healthcare professionals) | 1 | 9% |
Science communicators (journalists, bloggers, editors) | 1 | 9% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 23 | 7% |
Germany | 4 | 1% |
United Kingdom | 4 | 1% |
Kenya | 1 | <1% |
Brazil | 1 | <1% |
France | 1 | <1% |
Sweden | 1 | <1% |
Japan | 1 | <1% |
Denmark | 1 | <1% |
Other | 0 | 0% |
Unknown | 279 | 88% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 97 | 31% |
Student > Ph. D. Student | 56 | 18% |
Student > Master | 35 | 11% |
Student > Bachelor | 19 | 6% |
Professor | 16 | 5% |
Other | 48 | 15% |
Unknown | 45 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 119 | 38% |
Computer Science | 46 | 15% |
Biochemistry, Genetics and Molecular Biology | 37 | 12% |
Medicine and Dentistry | 15 | 5% |
Chemistry | 8 | 3% |
Other | 40 | 13% |
Unknown | 51 | 16% |