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OncodriveFML: a general framework to identify coding and non-coding regions with cancer driver mutations

Overview of attention for article published in Genome Biology, June 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

blogs
1 blog
twitter
40 X users

Citations

dimensions_citation
261 Dimensions

Readers on

mendeley
237 Mendeley
citeulike
5 CiteULike
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Title
OncodriveFML: a general framework to identify coding and non-coding regions with cancer driver mutations
Published in
Genome Biology, June 2016
DOI 10.1186/s13059-016-0994-0
Pubmed ID
Authors

Loris Mularoni, Radhakrishnan Sabarinathan, Jordi Deu-Pons, Abel Gonzalez-Perez, Núria López-Bigas

Abstract

Distinguishing the driver mutations from somatic mutations in a tumor genome is one of the major challenges of cancer research. This challenge is more acute and far from solved for non-coding mutations. Here we present OncodriveFML, a method designed to analyze the pattern of somatic mutations across tumors in both coding and non-coding genomic regions to identify signals of positive selection, and therefore, their involvement in tumorigenesis. We describe the method and illustrate its usefulness to identify protein-coding genes, promoters, untranslated regions, intronic splice regions, and lncRNAs-containing driver mutations in several malignancies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 40 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 237 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 <1%
China 1 <1%
Germany 1 <1%
Unknown 234 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 55 23%
Student > Ph. D. Student 52 22%
Student > Master 30 13%
Student > Bachelor 23 10%
Student > Doctoral Student 9 4%
Other 31 13%
Unknown 37 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 102 43%
Agricultural and Biological Sciences 46 19%
Medicine and Dentistry 16 7%
Computer Science 12 5%
Neuroscience 3 1%
Other 14 6%
Unknown 44 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 29. 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 14 August 2023.
All research outputs
#1,344,124
of 25,402,528 outputs
Outputs from Genome Biology
#1,051
of 4,470 outputs
Outputs of similar age
#24,074
of 353,478 outputs
Outputs of similar age from Genome Biology
#17
of 81 outputs
Altmetric has tracked 25,402,528 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,470 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 well, scoring higher than 76% 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 353,478 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 93% of its contemporaries.
We're also able to compare this research output to 81 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.