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A network modeling approach to elucidate drug resistance mechanisms and predict combinatorial drug treatments in breast cancer

Overview of attention for article published in Cancer Convergence, December 2017
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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 (84th percentile)

Mentioned by

blogs
1 blog
twitter
8 tweeters
facebook
2 Facebook pages

Citations

dimensions_citation
36 Dimensions

Readers on

mendeley
56 Mendeley
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Title
A network modeling approach to elucidate drug resistance mechanisms and predict combinatorial drug treatments in breast cancer
Published in
Cancer Convergence, December 2017
DOI 10.1186/s41236-017-0007-6
Authors

Jorge Gómez Tejeda Zañudo, Maurizio Scaltriti, Réka Albert

Twitter Demographics

The data shown below were collected from the profiles of 8 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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 30%
Student > Master 8 14%
Student > Bachelor 6 11%
Researcher 6 11%
Student > Doctoral Student 5 9%
Other 7 13%
Unknown 7 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 29%
Agricultural and Biological Sciences 13 23%
Mathematics 4 7%
Medicine and Dentistry 4 7%
Engineering 3 5%
Other 9 16%
Unknown 7 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 01 September 2020.
All research outputs
#2,152,718
of 18,792,779 outputs
Outputs from Cancer Convergence
#2
of 7 outputs
Outputs of similar age
#65,578
of 423,497 outputs
Outputs of similar age from Cancer Convergence
#2
of 4 outputs
Altmetric has tracked 18,792,779 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7 research outputs from this source. They receive a mean Attention Score of 4.7. This one scored the same or higher as 5 of them.
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 423,497 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 84% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.