| Title |
PredictSNP: Robust and Accurate Consensus Classifier for Prediction of Disease-Related Mutations
|
|---|---|
| Published in |
PLoS Computational Biology, January 2014
|
| DOI | 10.1371/journal.pcbi.1003440 |
| Pubmed ID | |
| Authors |
Jaroslav Bendl, Jan Stourac, Ondrej Salanda, Antonin Pavelka, Eric D. Wieben, Jaroslav Zendulka, Jan Brezovsky, Jiri Damborsky |
X Demographics
The data shown below were collected from the profiles of 24 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 | 8 | 33% |
| Spain | 2 | 8% |
| India | 1 | 4% |
| Argentina | 1 | 4% |
| Italy | 1 | 4% |
| China | 1 | 4% |
| Canada | 1 | 4% |
| United Kingdom | 1 | 4% |
| Sweden | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 7 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 14 | 58% |
| Members of the public | 9 | 38% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 506 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | <1% |
| Spain | 3 | <1% |
| Sweden | 2 | <1% |
| Canada | 2 | <1% |
| United Kingdom | 2 | <1% |
| Germany | 1 | <1% |
| Switzerland | 1 | <1% |
| Belgium | 1 | <1% |
| Brazil | 1 | <1% |
| Other | 2 | <1% |
| Unknown | 486 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 82 | 16% |
| Researcher | 67 | 13% |
| Student > Master | 65 | 13% |
| Student > Bachelor | 57 | 11% |
| Student > Postgraduate | 26 | 5% |
| Other | 83 | 16% |
| Unknown | 126 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 136 | 27% |
| Agricultural and Biological Sciences | 112 | 22% |
| Medicine and Dentistry | 27 | 5% |
| Computer Science | 23 | 5% |
| Engineering | 17 | 3% |
| Other | 53 | 10% |
| Unknown | 138 | 27% |