↓ Skip to main content

Cancer heterogeneity and multilayer spatial evolutionary games

Overview of attention for article published in Biology Direct, October 2016
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
15 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Cancer heterogeneity and multilayer spatial evolutionary games
Published in
Biology Direct, October 2016
DOI 10.1186/s13062-016-0156-z
Pubmed ID
Authors

Andrzej Świerniak, Michał Krześlak

Abstract

Evolutionary game theory (EGT) has been widely used to simulate tumour processes. In almost all studies on EGT models analysis is limited to two or three phenotypes. Our model contains four main phenotypes. Moreover, in a standard approach only heterogeneity of populations is studied, while cancer cells remain homogeneous. A multilayer approach proposed in this paper enables to study heterogeneity of single cells. In the extended model presented in this paper we consider four strategies (phenotypes) that can arise by mutations. We propose multilayer spatial evolutionary games (MSEG) played on multiple 2D lattices corresponding to the possible phenotypes. It enables simulation and investigation of heterogeneity on the player-level in addition to the population-level. Moreover, it allows to model interactions between arbitrary many phenotypes resulting from the mixture of basic traits. Different equilibrium points and scenarios (monomorphic and polymorphic populations) have been achieved depending on model parameters and the type of played game. However, there is a possibility of stable quadromorphic population in MSEG games for the same set of parameters like for the mean-field game. The model assumes an existence of four possible phenotypes (strategies) in the population of cells that make up tumour. Various parameters and relations between cells lead to complex analysis of this model and give diverse results. One of them is a possibility of stable coexistence of different tumour cells within the population, representing almost arbitrary mixture of the basic phenotypes. This article was reviewed by Tomasz Lipniacki, Urszula Ledzewicz and Jacek Banasiak.

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

Geographical breakdown

Country Count As %
France 1 7%
Unknown 14 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 27%
Student > Bachelor 4 27%
Researcher 2 13%
Lecturer 1 7%
Professor > Associate Professor 1 7%
Other 0 0%
Unknown 3 20%
Readers by discipline Count As %
Medicine and Dentistry 3 20%
Agricultural and Biological Sciences 3 20%
Biochemistry, Genetics and Molecular Biology 2 13%
Physics and Astronomy 2 13%
Social Sciences 1 7%
Other 1 7%
Unknown 3 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 20 October 2016.
All research outputs
#20,689,135
of 25,416,581 outputs
Outputs from Biology Direct
#447
of 537 outputs
Outputs of similar age
#251,465
of 325,771 outputs
Outputs of similar age from Biology Direct
#10
of 14 outputs
Altmetric has tracked 25,416,581 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 537 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one is in the 9th percentile – i.e., 9% 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 325,771 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 14 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.