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Mendeley readers
| Title |
GOAnnotator: linking protein GO annotations to evidence text
|
|---|---|
| Published in |
Journal of Biomedical Discovery and Collaboration, December 2006
|
| DOI | 10.1186/1747-5333-1-19 |
| Pubmed ID | |
| Authors |
Francisco M Couto, Mário J Silva, Vivian Lee, Emily Dimmer, Evelyn Camon, Rolf Apweiler, Harald Kirsch, Dietrich Rebholz-Schuhmann |
| Abstract |
Annotation of proteins with gene ontology (GO) terms is ongoing work and a complex task. Manual GO annotation is precise and precious, but it is time-consuming. Therefore, instead of curated annotations most of the proteins come with uncurated annotations, which have been generated automatically. Text-mining systems that use literature for automatic annotation have been proposed but they do not satisfy the high quality expectations of curators. |
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 % |
|---|---|---|
| United Kingdom | 2 | 6% |
| Spain | 2 | 6% |
| United States | 2 | 6% |
| Germany | 2 | 6% |
| Unknown | 24 | 75% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 31% |
| Student > Ph. D. Student | 6 | 19% |
| Professor > Associate Professor | 5 | 16% |
| Student > Bachelor | 2 | 6% |
| Student > Master | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 7 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 11 | 34% |
| Agricultural and Biological Sciences | 9 | 28% |
| Biochemistry, Genetics and Molecular Biology | 3 | 9% |
| Nursing and Health Professions | 1 | 3% |
| Chemistry | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 7 | 22% |