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Deciphering Epithelial–Mesenchymal Transition Regulatory Networks in Cancer through Computational Approaches

Overview of attention for article published in Frontiers in oncology, August 2017
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Title
Deciphering Epithelial–Mesenchymal Transition Regulatory Networks in Cancer through Computational Approaches
Published in
Frontiers in oncology, August 2017
DOI 10.3389/fonc.2017.00162
Pubmed ID
Authors

Gerhard A. Burger, Erik H. J. Danen, Joost B. Beltman

Abstract

Epithelial-mesenchymal transition (EMT), the process by which epithelial cells can convert into motile mesenchymal cells, plays an important role in development and wound healing but is also involved in cancer progression. It is increasingly recognized that EMT is a dynamic process involving multiple intermediate or "hybrid" phenotypes rather than an "all-or-none" process. However, the role of EMT in various cancer hallmarks, including metastasis, is debated. Given the complexity of EMT regulation, computational modeling has proven to be an invaluable tool for cancer research, i.e., to resolve apparent conflicts in experimental data and to guide experiments by generating testable hypotheses. In this review, we provide an overview of computational modeling efforts that have been applied to regulation of EMT in the context of cancer progression and its associated tumor characteristics. Moreover, we identify possibilities to bridge different modeling approaches and point out outstanding questions in which computational modeling can contribute to advance our understanding of pathological EMT.

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

Geographical breakdown

Country Count As %
Unknown 95 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 19 20%
Student > Master 17 18%
Student > Ph. D. Student 15 16%
Researcher 10 11%
Student > Doctoral Student 4 4%
Other 7 7%
Unknown 23 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 23 24%
Agricultural and Biological Sciences 15 16%
Medicine and Dentistry 8 8%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Engineering 4 4%
Other 12 13%
Unknown 29 31%
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 22 August 2017.
All research outputs
#20,660,571
of 25,382,440 outputs
Outputs from Frontiers in oncology
#11,318
of 22,428 outputs
Outputs of similar age
#253,170
of 327,246 outputs
Outputs of similar age from Frontiers in oncology
#55
of 84 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,428 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 29th percentile – i.e., 29% 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 327,246 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 84 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.