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Mendeley readers
| Title |
Strategies for analyzing highly enriched IP-chip datasets
|
|---|---|
| Published in |
BMC Bioinformatics, September 2009
|
| DOI | 10.1186/1471-2105-10-305 |
| Pubmed ID | |
| Authors |
Simon RV Knott, Christopher J Viggiani, Oscar M Aparicio, Simon Tavaré |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 22% |
| United Kingdom | 1 | 6% |
| Denmark | 1 | 6% |
| Unknown | 12 | 67% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 28% |
| Researcher | 3 | 17% |
| Other | 2 | 11% |
| Professor | 2 | 11% |
| Student > Doctoral Student | 1 | 6% |
| Other | 4 | 22% |
| Unknown | 1 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 61% |
| Biochemistry, Genetics and Molecular Biology | 2 | 11% |
| Engineering | 2 | 11% |
| Computer Science | 1 | 6% |
| Chemical Engineering | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 1 | 6% |