Title |
Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical Properties
|
---|---|
Published in |
PLOS ONE, April 2013
|
DOI | 10.1371/journal.pone.0061318 |
Pubmed ID | |
Authors |
Michael P. Menden, Francesco Iorio, Mathew Garnett, Ultan McDermott, Cyril H. Benes, Pedro J. Ballester, Julio Saez-Rodriguez |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 25% |
United States | 2 | 17% |
Korea, Republic of | 1 | 8% |
Canada | 1 | 8% |
Spain | 1 | 8% |
Germany | 1 | 8% |
Switzerland | 1 | 8% |
Unknown | 2 | 17% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 7 | 58% |
Members of the public | 5 | 42% |
Mendeley readers
The data shown below were compiled from readership statistics for 623 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 10 | 2% |
Germany | 4 | <1% |
United Kingdom | 3 | <1% |
India | 2 | <1% |
Denmark | 2 | <1% |
Austria | 1 | <1% |
Canada | 1 | <1% |
Italy | 1 | <1% |
Spain | 1 | <1% |
Other | 1 | <1% |
Unknown | 597 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 155 | 25% |
Researcher | 93 | 15% |
Student > Master | 77 | 12% |
Student > Bachelor | 59 | 9% |
Student > Postgraduate | 28 | 4% |
Other | 95 | 15% |
Unknown | 116 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 124 | 20% |
Computer Science | 105 | 17% |
Biochemistry, Genetics and Molecular Biology | 93 | 15% |
Engineering | 38 | 6% |
Medicine and Dentistry | 29 | 5% |
Other | 107 | 17% |
Unknown | 127 | 20% |