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The `dnet’ approach promotes emerging research on cancer patient survival

Overview of attention for article published in Genome Medicine, August 2014
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1 X user

Citations

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67 Dimensions

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70 Mendeley
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Title
The `dnet’ approach promotes emerging research on cancer patient survival
Published in
Genome Medicine, August 2014
DOI 10.1186/s13073-014-0064-8
Pubmed ID
Authors

Hai Fang, Julian Gough

Abstract

We present the 'dnet' package and apply it to the 'TCGA' mutation and clinical data of >3,000 patients. We uncover the existence of an underlying gene network that at least partially controls cancer 'survivalness', with mutations that are significantly correlated with patient survival, yet independent of tumour origin and type. The survivalness network has natural community structure corresponding to tumour hallmarks, and contains genes that are potentially druggable in the clinic. This network has evolutionary roots in Deuterostomia identifying PTK2 and VAV1 as under-valued relative to more studied genes from that era. The 'dnet' R package is available at http://cran.r-project.org/package=dnet.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 3%
Sweden 1 1%
Germany 1 1%
Romania 1 1%
United States 1 1%
Unknown 64 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 29%
Student > Master 9 13%
Student > Ph. D. Student 7 10%
Professor 5 7%
Professor > Associate Professor 4 6%
Other 12 17%
Unknown 13 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 29%
Biochemistry, Genetics and Molecular Biology 12 17%
Medicine and Dentistry 9 13%
Computer Science 6 9%
Engineering 4 6%
Other 5 7%
Unknown 14 20%
Attention Score in Context

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 31 January 2016.
All research outputs
#17,700,438
of 25,837,817 outputs
Outputs from Genome Medicine
#1,470
of 1,611 outputs
Outputs of similar age
#153,340
of 249,181 outputs
Outputs of similar age from Genome Medicine
#27
of 33 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,611 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.6. This one is in the 5th percentile – i.e., 5% 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 249,181 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.