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Mendeley readers
| Title |
Ultra-high throughput sequencing-based small RNA discovery and discrete statistical biomarker analysis in a collection of cervical tumours and matched controls
|
|---|---|
| Published in |
BMC Biology, May 2010
|
| DOI | 10.1186/1741-7007-8-58 |
| Pubmed ID | |
| Authors |
Daniela Witten, Robert Tibshirani, Sam Guoping Gu, Andrew Fire, Weng-Onn Lui |
| Abstract |
Ultra-high throughput sequencing technologies provide opportunities both for discovery of novel molecular species and for detailed comparisons of gene expression patterns. Small RNA populations are particularly well suited to this analysis, as many different small RNAs can be completely sequenced in a single instrument run. |
Mendeley readers
The data shown below were compiled from readership statistics for 198 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 2% |
| Sweden | 2 | 1% |
| Italy | 1 | <1% |
| France | 1 | <1% |
| Germany | 1 | <1% |
| Belgium | 1 | <1% |
| United Kingdom | 1 | <1% |
| Spain | 1 | <1% |
| Luxembourg | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 186 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 54 | 27% |
| Student > Ph. D. Student | 50 | 25% |
| Student > Bachelor | 18 | 9% |
| Student > Master | 16 | 8% |
| Professor > Associate Professor | 10 | 5% |
| Other | 28 | 14% |
| Unknown | 22 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 97 | 49% |
| Biochemistry, Genetics and Molecular Biology | 27 | 14% |
| Medicine and Dentistry | 19 | 10% |
| Mathematics | 8 | 4% |
| Computer Science | 6 | 3% |
| Other | 16 | 8% |
| Unknown | 25 | 13% |