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American Association for Cancer Research

The Functional Landscape of Patient-Derived RNF43 Mutations Predicts Sensitivity to Wnt Inhibition

Overview of attention for article published in Cancer Research, December 2020
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

news
8 news outlets
blogs
1 blog
twitter
1 X user

Citations

dimensions_citation
33 Dimensions

Readers on

mendeley
36 Mendeley
Title
The Functional Landscape of Patient-Derived RNF43 Mutations Predicts Sensitivity to Wnt Inhibition
Published in
Cancer Research, December 2020
DOI 10.1158/0008-5472.can-20-0957
Pubmed ID
Authors

Jia Yu, Permeen A Mohamed Yusoff, Daniëlle T J Woutersen, Pamela Goh, Nathan Harmston, Ron Smits, David M Epstein, David M Virshup, Babita Madan

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 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 14%
Student > Ph. D. Student 5 14%
Other 3 8%
Student > Doctoral Student 2 6%
Student > Bachelor 2 6%
Other 6 17%
Unknown 13 36%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 28%
Medicine and Dentistry 5 14%
Agricultural and Biological Sciences 3 8%
Unspecified 2 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 4 11%
Unknown 11 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 67. 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 16 December 2020.
All research outputs
#556,931
of 23,257,423 outputs
Outputs from Cancer Research
#332
of 18,027 outputs
Outputs of similar age
#16,430
of 506,056 outputs
Outputs of similar age from Cancer Research
#15
of 187 outputs
Altmetric has tracked 23,257,423 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 18,027 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.8. This one has done particularly well, scoring higher than 98% 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 506,056 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 96% of its contemporaries.
We're also able to compare this research output to 187 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.