Data Mining Techniques for the Life Sciences
Springer New York
Title |
Data Mining Techniques for the Life Sciences
|
---|---|
Published by |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3572-7 |
ISBNs |
978-1-4939-3570-3, 978-1-4939-3572-7
|
Editors |
Oliviero Carugo, Frank Eisenhaber |
Country | Count | As % |
---|---|---|
United States | 6 | 15% |
France | 4 | 10% |
United Kingdom | 3 | 8% |
Greece | 2 | 5% |
Netherlands | 1 | 3% |
Australia | 1 | 3% |
Canada | 1 | 3% |
Germany | 1 | 3% |
Unknown | 21 | 53% |
Type | Count | As % |
---|---|---|
Members of the public | 24 | 60% |
Scientists | 16 | 40% |
Country | Count | As % |
---|---|---|
Unknown | 26 | 100% |
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 6 | 23% |
Researcher | 4 | 15% |
Student > Ph. D. Student | 4 | 15% |
Student > Bachelor | 3 | 12% |
Other | 2 | 8% |
Other | 1 | 4% |
Unknown | 6 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 6 | 23% |
Agricultural and Biological Sciences | 4 | 15% |
Computer Science | 2 | 8% |
Engineering | 2 | 8% |
Mathematics | 1 | 4% |
Other | 5 | 19% |
Unknown | 6 | 23% |