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Mendeley readers
| Title |
Machine learning based analyses on metabolic networks supports high-throughput knockout screens
|
|---|---|
| Published in |
BMC Systems Biology, July 2008
|
| DOI | 10.1186/1752-0509-2-67 |
| Pubmed ID | |
| Authors |
Kitiporn Plaimas, Jan-Phillip Mallm, Marcus Oswald, Fabian Svara, Victor Sourjik, Roland Eils, Rainer König |
Mendeley readers
The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Colombia | 1 | <1% |
| Germany | 1 | <1% |
| France | 1 | <1% |
| India | 1 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 96 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 23% |
| Researcher | 19 | 19% |
| Student > Bachelor | 10 | 10% |
| Professor > Associate Professor | 8 | 8% |
| Student > Master | 8 | 8% |
| Other | 18 | 18% |
| Unknown | 16 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 35 | 34% |
| Biochemistry, Genetics and Molecular Biology | 16 | 16% |
| Computer Science | 14 | 14% |
| Engineering | 7 | 7% |
| Mathematics | 3 | 3% |
| Other | 4 | 4% |
| Unknown | 23 | 23% |