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Cancer prognosis prediction using somatic point mutation and copy number variation data: a comparison of gene-level and pathway-based models

Overview of attention for article published in BMC Bioinformatics, October 2020
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Mentioned by

twitter
4 tweeters

Citations

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5 Dimensions

Readers on

mendeley
17 Mendeley
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Title
Cancer prognosis prediction using somatic point mutation and copy number variation data: a comparison of gene-level and pathway-based models
Published in
BMC Bioinformatics, October 2020
DOI 10.1186/s12859-020-03791-0
Authors

Xingyu Zheng, Christopher I. Amos, H. Robert Frost

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 41%
Student > Master 5 29%
Student > Postgraduate 1 6%
Student > Ph. D. Student 1 6%
Unknown 3 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 53%
Chemical Engineering 1 6%
Computer Science 1 6%
Psychology 1 6%
Social Sciences 1 6%
Other 1 6%
Unknown 3 18%

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 30 July 2021.
All research outputs
#13,409,855
of 20,141,442 outputs
Outputs from BMC Bioinformatics
#4,896
of 6,736 outputs
Outputs of similar age
#243,412
of 391,671 outputs
Outputs of similar age from BMC Bioinformatics
#369
of 484 outputs
Altmetric has tracked 20,141,442 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,736 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 19th percentile – i.e., 19% 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 391,671 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 484 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.