| Title |
Integrated Analyses of microRNAs Demonstrate Their Widespread Influence on Gene Expression in High-Grade Serous Ovarian Carcinoma
|
|---|---|
| Published in |
PLOS ONE, March 2012
|
| DOI | 10.1371/journal.pone.0034546 |
| Pubmed ID | |
| Authors |
Chad J. Creighton, Anadulce Hernandez-Herrera, Anders Jacobsen, Douglas A. Levine, Parminder Mankoo, Nikolaus Schultz, Ying Du, Yiqun Zhang, Erik Larsson, Robert Sheridan, Weimin Xiao, Paul T. Spellman, Gad Getz, David A. Wheeler, Charles M. Perou, Richard A. Gibbs, Chris Sander, D. Neil Hayes, Preethi H. Gunaratne |
| Abstract |
The Cancer Genome Atlas (TCGA) Network recently comprehensively catalogued the molecular aberrations in 487 high-grade serous ovarian cancers, with much remaining to be elucidated regarding the microRNAs (miRNAs). Here, using TCGA ovarian data, we surveyed the miRNAs, in the context of their predicted gene targets. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 1 | 50% |
| Germany | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 5% |
| Belgium | 1 | <1% |
| Switzerland | 1 | <1% |
| China | 1 | <1% |
| Nigeria | 1 | <1% |
| Unknown | 123 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 38 | 29% |
| Student > Ph. D. Student | 31 | 23% |
| Student > Bachelor | 12 | 9% |
| Student > Master | 10 | 8% |
| Other | 8 | 6% |
| Other | 18 | 14% |
| Unknown | 16 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 66 | 50% |
| Medicine and Dentistry | 22 | 17% |
| Biochemistry, Genetics and Molecular Biology | 12 | 9% |
| Engineering | 4 | 3% |
| Computer Science | 4 | 3% |
| Other | 9 | 7% |
| Unknown | 16 | 12% |