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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Integrated Analysis of Gene Expression and Tumor Nuclear Image Profiles Associated with Chemotherapy Response in Serous Ovarian Carcinoma
|
|---|---|
| Published in |
PLOS ONE, May 2012
|
| DOI | 10.1371/journal.pone.0036383 |
| Pubmed ID | |
| Authors |
Yuexin Liu, Yan Sun, Russell Broaddus, Jinsong Liu, Anil K. Sood, Ilya Shmulevich, Wei Zhang |
| Abstract |
Small sample sizes used in previous studies result in a lack of overlap between the reported gene signatures for prediction of chemotherapy response. Although morphologic features, especially tumor nuclear morphology, are important for cancer grading, little research has been reported on quantitatively correlating cellular morphology with chemotherapy response, especially in a large data set. In this study, we have used a large population of patients to identify molecular and morphologic signatures associated with chemotherapy response in serous ovarian carcinoma. |
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 | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 2% |
| Czechia | 1 | 2% |
| Unknown | 43 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 33% |
| Student > Ph. D. Student | 12 | 27% |
| Professor > Associate Professor | 4 | 9% |
| Other | 3 | 7% |
| Student > Bachelor | 2 | 4% |
| Other | 7 | 16% |
| Unknown | 2 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 24% |
| Medicine and Dentistry | 10 | 22% |
| Computer Science | 8 | 18% |
| Biochemistry, Genetics and Molecular Biology | 7 | 16% |
| Chemistry | 2 | 4% |
| Other | 3 | 7% |
| Unknown | 4 | 9% |
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 07 August 2014.
All research outputs
#6,246,005
of 22,665,794 outputs
Outputs from PLOS ONE
#74,620
of 193,511 outputs
Outputs of similar age
#43,509
of 163,481 outputs
Outputs of similar age from PLOS ONE
#1,184
of 3,797 outputs
Altmetric has tracked 22,665,794 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 193,511 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 60% 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 163,481 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 3,797 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 68% of its contemporaries.