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Mendeley readers
| Title |
CGMIM: Automated text-mining of Online Mendelian Inheritance in Man (OMIM) to identify genetically-associated cancers and candidate genes
|
|---|---|
| Published in |
BMC Bioinformatics, March 2005
|
| DOI | 10.1186/1471-2105-6-78 |
| Pubmed ID | |
| Authors |
Chris D Bajdik, Byron Kuo, Shawn Rusaw, Steven Jones, Angela Brooks-Wilson |
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 % |
|---|---|---|
| United Kingdom | 3 | 6% |
| United States | 2 | 4% |
| Unknown | 46 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 27% |
| Student > Ph. D. Student | 7 | 14% |
| Student > Master | 4 | 8% |
| Other | 4 | 8% |
| Student > Doctoral Student | 2 | 4% |
| Other | 6 | 12% |
| Unknown | 14 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 14 | 27% |
| Biochemistry, Genetics and Molecular Biology | 6 | 12% |
| Medicine and Dentistry | 6 | 12% |
| Computer Science | 6 | 12% |
| Mathematics | 1 | 2% |
| Other | 4 | 8% |
| Unknown | 14 | 27% |