| Title |
CAERUS: Predicting CAncER oUtcomeS Using Relationship between Protein Structural Information, Protein Networks, Gene Expression Data, and Mutation Data
|
|---|---|
| Published in |
PLoS Computational Biology, March 2011
|
| DOI | 10.1371/journal.pcbi.1001114 |
| Pubmed ID | |
| Authors |
Kelvin Xi Zhang, B. F. Francis Ouellette |
Mendeley readers
The data shown below were compiled from readership statistics for 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 5% |
| Canada | 2 | 2% |
| Brazil | 1 | 1% |
| France | 1 | 1% |
| Germany | 1 | 1% |
| Belgium | 1 | 1% |
| Egypt | 1 | 1% |
| Spain | 1 | 1% |
| China | 1 | 1% |
| Other | 0 | 0% |
| Unknown | 82 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 31 | 32% |
| Student > Ph. D. Student | 22 | 23% |
| Professor > Associate Professor | 9 | 9% |
| Professor | 7 | 7% |
| Other | 6 | 6% |
| Other | 15 | 16% |
| Unknown | 6 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 40 | 42% |
| Computer Science | 12 | 13% |
| Medicine and Dentistry | 12 | 13% |
| Biochemistry, Genetics and Molecular Biology | 12 | 13% |
| Engineering | 3 | 3% |
| Other | 8 | 8% |
| Unknown | 9 | 9% |