| Title |
Predicting commercially available antiviral drugs that may act on the novel coronavirus (2019-nCoV), Wuhan, China through a drug-target interaction deep learning model
|
|---|---|
| Published in |
bioRxiv, February 2020
|
| DOI | 10.1101/2020.01.31.929547 |
| Authors |
Bo Ram Beck, Bonggun Shin, Yoonjung Choi, Sungsoo Park, Keunsoo Kang |
X Demographics
The data shown below were collected from the profiles of 84 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 States | 24 | 29% |
| Canada | 2 | 2% |
| France | 2 | 2% |
| Sweden | 2 | 2% |
| Comoros | 2 | 2% |
| Mongolia | 1 | 1% |
| Switzerland | 1 | 1% |
| Thailand | 1 | 1% |
| Argentina | 1 | 1% |
| Other | 8 | 10% |
| Unknown | 40 | 48% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 73 | 87% |
| Scientists | 7 | 8% |
| Practitioners (doctors, other healthcare professionals) | 3 | 4% |
| Science communicators (journalists, bloggers, editors) | 1 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 111 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 19% |
| Student > Master | 17 | 15% |
| Student > Ph. D. Student | 14 | 13% |
| Student > Bachelor | 12 | 11% |
| Student > Doctoral Student | 7 | 6% |
| Other | 17 | 15% |
| Unknown | 23 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 15 | 14% |
| Chemistry | 13 | 12% |
| Biochemistry, Genetics and Molecular Biology | 12 | 11% |
| Computer Science | 8 | 7% |
| Agricultural and Biological Sciences | 7 | 6% |
| Other | 26 | 23% |
| Unknown | 30 | 27% |