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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Genome-Scale Screen for DNA Methylation-Based Detection Markers for Ovarian Cancer
|
|---|---|
| Published in |
PLOS ONE, December 2011
|
| DOI | 10.1371/journal.pone.0028141 |
| Pubmed ID | |
| Authors |
Mihaela Campan, Melissa Moffitt, Sahar Houshdaran, Hui Shen, Martin Widschwendter, Günter Daxenbichler, Tiffany Long, Christian Marth, Ite A. Laird-Offringa, Michael F. Press, Louis Dubeau, Kimberly D. Siegmund, Anna H. Wu, Susan Groshen, Uma Chandavarkar, Lynda D. Roman, Andrew Berchuck, Celeste L. Pearce, Peter W. Laird |
| Abstract |
The identification of sensitive biomarkers for the detection of ovarian cancer is of high clinical relevance for early detection and/or monitoring of disease recurrence. We developed a systematic multi-step biomarker discovery and verification strategy to identify candidate DNA methylation markers for the blood-based detection of ovarian cancer. |
X Demographics
The data shown below were collected from the profiles of 3 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 | 2 | 67% |
| Australia | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 9% |
| Sweden | 1 | 2% |
| Unknown | 52 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 22% |
| Student > Ph. D. Student | 12 | 21% |
| Student > Bachelor | 8 | 14% |
| Student > Doctoral Student | 4 | 7% |
| Professor > Associate Professor | 4 | 7% |
| Other | 9 | 16% |
| Unknown | 8 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 29 | 50% |
| Medicine and Dentistry | 11 | 19% |
| Biochemistry, Genetics and Molecular Biology | 9 | 16% |
| Computer Science | 1 | 2% |
| Mathematics | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 7 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 June 2013.
All research outputs
#5,846,113
of 22,659,164 outputs
Outputs from PLOS ONE
#69,924
of 193,435 outputs
Outputs of similar age
#51,660
of 240,804 outputs
Outputs of similar age from PLOS ONE
#747
of 2,869 outputs
Altmetric has tracked 22,659,164 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 193,435 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one has gotten more attention than average, scoring higher than 63% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 240,804 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 2,869 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.