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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Combined image and genomic analysis of high-grade serous ovarian cancer reveals PTEN loss as a common driver event and prognostic classifier
|
|---|---|
| Published in |
Genome Biology, December 2014
|
| DOI | 10.1186/s13059-014-0526-8 |
| Pubmed ID | |
| Authors |
Filipe C Martins, Ines de Santiago, Anne Trinh, Jian Xian, Anne Guo, Karen Sayal, Mercedes Jimenez-Linan, Suha Deen, Kristy Driver, Marie Mack, Jennifer Aslop, Paul D Pharoah, Florian Markowetz, James D Brenton |
| Abstract |
TP53 and BRCA1/2 mutations are the main drivers in high-grade serous ovarian carcinoma (HGSOC). We hypothesise that combining tissue phenotypes from image analysis of tumour sections with genomic profiles could reveal other significant driver events. |
X Demographics
The data shown below were collected from the profiles of 20 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 | 5 | 25% |
| United Kingdom | 5 | 25% |
| France | 1 | 5% |
| India | 1 | 5% |
| Unknown | 8 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 9 | 45% |
| Members of the public | 9 | 45% |
| Science communicators (journalists, bloggers, editors) | 2 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 5 | 4% |
| United States | 2 | 2% |
| Norway | 1 | <1% |
| Germany | 1 | <1% |
| Brazil | 1 | <1% |
| Switzerland | 1 | <1% |
| Unknown | 117 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 35 | 27% |
| Researcher | 23 | 18% |
| Student > Bachelor | 14 | 11% |
| Student > Master | 11 | 9% |
| Student > Doctoral Student | 6 | 5% |
| Other | 21 | 16% |
| Unknown | 18 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 30 | 23% |
| Medicine and Dentistry | 24 | 19% |
| Biochemistry, Genetics and Molecular Biology | 24 | 19% |
| Computer Science | 11 | 9% |
| Mathematics | 3 | 2% |
| Other | 13 | 10% |
| Unknown | 23 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 66. 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 04 April 2016.
All research outputs
#649,057
of 25,374,917 outputs
Outputs from Genome Biology
#402
of 4,467 outputs
Outputs of similar age
#7,657
of 347,660 outputs
Outputs of similar age from Genome Biology
#9
of 99 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done particularly well, scoring higher than 91% 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 347,660 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 99 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.