Game theory cancer models of cancer cell-stromal cell dynamics using interacting particle systems

Yinan Zheng; Yusha Sun; Gonzalo Torga; Kenneth Pienta; Robert Austin

doi:10.1142/9789811223495_0002

Game theory cancer models of cancer cell-stromal cell dynamics using interacting particle systems

Yinan Zheng, Yusha Sun, Gonzalo Torga, Kenneth Pienta, Robert Austin

School of Medicine

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

We describe an evolutionary game theory model that has been used to predict the population dynamics of interacting cancer and stromal cells. We first consider the mean field case assuming homogeneous and nondiscrete populations. Interacting Particle Systems (IPS) are then presented as a discrete and spatial alternative to the mean fild approach. Finally, we discuss cases where IPS gives results different from the mean field approach.

Original language	English (US)
Title of host publication	Physics Of Cancer, The
Subtitle of host publication	Research Advances
Publisher	World Scientific Publishing Co.
Pages	39-61
Number of pages	23
ISBN (Electronic)	9789811223495
DOIs	https://doi.org/10.1142/9789811223495_0002
State	Published - Jan 1 2020

Keywords

Cancer
Evolutionary game theory
Interacting particle systems
Population dynamics

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology(all)
Physics and Astronomy(all)

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10.1142/9789811223495_0002

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title = "Game theory cancer models of cancer cell-stromal cell dynamics using interacting particle systems",

abstract = "We describe an evolutionary game theory model that has been used to predict the population dynamics of interacting cancer and stromal cells. We first consider the mean field case assuming homogeneous and nondiscrete populations. Interacting Particle Systems (IPS) are then presented as a discrete and spatial alternative to the mean fild approach. Finally, we discuss cases where IPS gives results different from the mean field approach.",

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AU - Sun, Yusha

AU - Torga, Gonzalo

AU - Pienta, Kenneth

AU - Austin, Robert

PY - 2020/1/1

Y1 - 2020/1/1

N2 - We describe an evolutionary game theory model that has been used to predict the population dynamics of interacting cancer and stromal cells. We first consider the mean field case assuming homogeneous and nondiscrete populations. Interacting Particle Systems (IPS) are then presented as a discrete and spatial alternative to the mean fild approach. Finally, we discuss cases where IPS gives results different from the mean field approach.

AB - We describe an evolutionary game theory model that has been used to predict the population dynamics of interacting cancer and stromal cells. We first consider the mean field case assuming homogeneous and nondiscrete populations. Interacting Particle Systems (IPS) are then presented as a discrete and spatial alternative to the mean fild approach. Finally, we discuss cases where IPS gives results different from the mean field approach.

KW - Cancer

KW - Evolutionary game theory

KW - Interacting particle systems

KW - Population dynamics

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PB - World Scientific Publishing Co.

ER -

Game theory cancer models of cancer cell-stromal cell dynamics using interacting particle systems

Abstract

Keywords

ASJC Scopus subject areas

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