| Title |
Strong Inference for Systems Biology
|
|---|---|
| Published in |
PLoS Computational Biology, August 2009
|
| DOI | 10.1371/journal.pcbi.1000459 |
| Pubmed ID | |
| Authors |
Daniel A. Beard, Martin J. Kushmerick |
Mendeley readers
The data shown below were compiled from readership statistics for 143 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 11 | 8% |
| United Kingdom | 4 | 3% |
| France | 2 | 1% |
| Germany | 1 | <1% |
| Switzerland | 1 | <1% |
| Italy | 1 | <1% |
| Australia | 1 | <1% |
| Portugal | 1 | <1% |
| Sweden | 1 | <1% |
| Other | 3 | 2% |
| Unknown | 117 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 46 | 32% |
| Student > Ph. D. Student | 33 | 23% |
| Professor | 16 | 11% |
| Professor > Associate Professor | 16 | 11% |
| Student > Postgraduate | 7 | 5% |
| Other | 19 | 13% |
| Unknown | 6 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 66 | 46% |
| Engineering | 13 | 9% |
| Biochemistry, Genetics and Molecular Biology | 11 | 8% |
| Computer Science | 8 | 6% |
| Medicine and Dentistry | 6 | 4% |
| Other | 26 | 18% |
| Unknown | 13 | 9% |