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X Demographics
Mendeley readers
Attention Score in Context
Title |
Preliminary evidence of different selection pressures on cancer cells as compared to normal tissues
|
---|---|
Published in |
Theoretical Biology and Medical Modelling, November 2012
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DOI | 10.1186/1742-4682-9-44 |
Pubmed ID | |
Authors |
Katie Ovens, Christopher Naugler |
Abstract |
Cancer is characterized by both a high mutation rate as well as high rates of cell division and cell death. We postulate that these conditions will result in the eventual mutational inactivation of genes not essential to the survival of the cancer cell, while mutations in essential genes will be eliminated by natural selection leaving molecular signatures of selection in genes required for survival and reproduction. By looking for signatures of natural selection in the genomes of cancer cells, it should therefore be possible to determine which genes have been essential for the development of a particular cancer. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Peru | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 1 | 3% |
Poland | 1 | 3% |
Australia | 1 | 3% |
Brazil | 1 | 3% |
Unknown | 36 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 8 | 20% |
Researcher | 7 | 18% |
Student > Ph. D. Student | 6 | 15% |
Student > Postgraduate | 4 | 10% |
Student > Master | 2 | 5% |
Other | 2 | 5% |
Unknown | 11 | 28% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 10 | 25% |
Biochemistry, Genetics and Molecular Biology | 9 | 23% |
Medicine and Dentistry | 4 | 10% |
Environmental Science | 1 | 3% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
Other | 4 | 10% |
Unknown | 11 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 12 November 2012.
All research outputs
#18,323,689
of 22,689,790 outputs
Outputs from Theoretical Biology and Medical Modelling
#215
of 287 outputs
Outputs of similar age
#136,776
of 179,647 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#6
of 7 outputs
Altmetric has tracked 22,689,790 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 287 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
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 179,647 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one.