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Mendeley readers
| Title |
Mining protein function from text using term-based support vector machines
|
|---|---|
| Published in |
BMC Bioinformatics, May 2005
|
| DOI | 10.1186/1471-2105-6-s1-s22 |
| Pubmed ID | |
| Authors |
Simon B Rice, Goran Nenadic, Benjamin J Stapley |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 10% |
| Spain | 2 | 4% |
| Canada | 1 | 2% |
| Japan | 1 | 2% |
| New Caledonia | 1 | 2% |
| Unknown | 40 | 80% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 22% |
| Student > Ph. D. Student | 10 | 20% |
| Student > Master | 5 | 10% |
| Professor | 4 | 8% |
| Professor > Associate Professor | 4 | 8% |
| Other | 10 | 20% |
| Unknown | 6 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 18 | 36% |
| Agricultural and Biological Sciences | 10 | 20% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Engineering | 3 | 6% |
| Medicine and Dentistry | 3 | 6% |
| Other | 3 | 6% |
| Unknown | 10 | 20% |