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Controlled Breast Cancer Microarrays for the Deconvolution of Cellular Multilayering and Density Effects upon Drug Responses

Overview of attention for article published in PLOS ONE, June 2012
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Title
Controlled Breast Cancer Microarrays for the Deconvolution of Cellular Multilayering and Density Effects upon Drug Responses
Published in
PLOS ONE, June 2012
DOI 10.1371/journal.pone.0040141
Pubmed ID
Authors

Maria Håkanson, Stefan Kobel, Matthias P. Lutolf, Marcus Textor, Edna Cukierman, Mirren Charnley

Abstract

Increasing evidence shows that the cancer microenvironment affects both tumorigenesis and the response of cancer to drug treatment. Therefore in vitro models that selectively reflect characteristics of the in vivo environment are greatly needed. Current methods allow us to screen the effect of extrinsic parameters such as matrix composition and to model the complex and three-dimensional (3D) cancer environment. However, 3D models that reflect characteristics of the in vivo environment are typically too complex and do not allow the separation of discrete extrinsic parameters.

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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 %
United States 3 8%
United Kingdom 1 3%
Unknown 32 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 39%
Researcher 6 17%
Student > Bachelor 3 8%
Student > Doctoral Student 3 8%
Professor > Associate Professor 3 8%
Other 4 11%
Unknown 3 8%
Readers by discipline Count As %
Engineering 10 28%
Agricultural and Biological Sciences 8 22%
Biochemistry, Genetics and Molecular Biology 4 11%
Materials Science 4 11%
Medicine and Dentistry 3 8%
Other 2 6%
Unknown 5 14%
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 01 July 2012.
All research outputs
#18,309,495
of 22,669,724 outputs
Outputs from PLOS ONE
#153,778
of 193,515 outputs
Outputs of similar age
#126,274
of 164,182 outputs
Outputs of similar age from PLOS ONE
#3,128
of 3,987 outputs
Altmetric has tracked 22,669,724 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 193,515 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one is in the 10th percentile – i.e., 10% 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 164,182 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3,987 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.