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X Demographics
Mendeley readers
Attention Score in Context
Title |
Distinguishing between driver and passenger mutations in individual cancer genomes by network enrichment analysis
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Published in |
BMC Bioinformatics, September 2014
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DOI | 10.1186/1471-2105-15-308 |
Pubmed ID | |
Authors |
Simon Kebede Merid, Daria Goranskaya, Andrey Alexeyenko |
Abstract |
In somatic cancer genomes, delineating genuine driver mutations against a background of multiple passenger events is a challenging task. The difficulty of determining function from sequence data and the low frequency of mutations are increasingly hindering the search for novel, less common cancer drivers. The accumulation of extensive amounts of data on somatic point and copy number alterations necessitates the development of systematic methods for driver mutation analysis. |
X Demographics
The data shown below were collected from the profiles of 13 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 | 3 | 23% |
Australia | 2 | 15% |
Spain | 1 | 8% |
Germany | 1 | 8% |
Sweden | 1 | 8% |
Japan | 1 | 8% |
Unknown | 4 | 31% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 8 | 62% |
Scientists | 5 | 38% |
Mendeley readers
The data shown below were compiled from readership statistics for 178 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 1% |
United Kingdom | 1 | <1% |
Sweden | 1 | <1% |
Portugal | 1 | <1% |
Unknown | 173 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 36 | 20% |
Researcher | 31 | 17% |
Student > Bachelor | 22 | 12% |
Student > Master | 22 | 12% |
Student > Postgraduate | 14 | 8% |
Other | 29 | 16% |
Unknown | 24 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 53 | 30% |
Agricultural and Biological Sciences | 49 | 28% |
Medicine and Dentistry | 22 | 12% |
Computer Science | 11 | 6% |
Pharmacology, Toxicology and Pharmaceutical Science | 3 | 2% |
Other | 11 | 6% |
Unknown | 29 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 28 September 2014.
All research outputs
#4,594,331
of 22,764,165 outputs
Outputs from BMC Bioinformatics
#1,762
of 7,273 outputs
Outputs of similar age
#50,622
of 250,225 outputs
Outputs of similar age from BMC Bioinformatics
#30
of 111 outputs
Altmetric has tracked 22,764,165 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,273 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 75% 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 250,225 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 79% of its contemporaries.
We're also able to compare this research output to 111 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 71% of its contemporaries.