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Spatiotemporal modeling of cancer im...
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Schiesser, William E.
Spatiotemporal modeling of cancer immunotherapypartial differential equation analysis in R /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Spatiotemporal modeling of cancer immunotherapyby William E. Schiesser.
Reminder of title:
partial differential equation analysis in R /
Author:
Schiesser, William E.
Published:
Cham :Springer International Publishing :2019.
Description:
viii, 112 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
CancerImmunotherapy
Online resource:
https://doi.org/10.1007/978-3-030-19080-4
ISBN:
9783030190804$q(electronic bk.)
Spatiotemporal modeling of cancer immunotherapypartial differential equation analysis in R /
Schiesser, William E.
Spatiotemporal modeling of cancer immunotherapy
partial differential equation analysis in R /[electronic resource] :by William E. Schiesser. - Cham :Springer International Publishing :2019. - viii, 112 p. :ill., digital ;24 cm.
Fixed Boundary PDE Model Formulation -- Fixed Boundary PDE Model Implementation -- Fixed Boundary PDE Model Output -- Moving Boundary PDE Model Implementation -- Moving Boundary PDE Model Output -- Index.
The focus of this book is a detailed discussion of a dual cancer vaccine (CV)-immune checkpoint inhibitor (ICI) mathematical model formulated as a system of partial differential equations (PDEs) defining the spatiotemporal distribution of cells and biochemicals during tumor growth. A computer implementation of the model is discussed in detail for the quantitative evaluation of CV-ICI therapy. The coding (programming) consists of a series of routines in R, a quality, open-source scientific computing system that is readily available from the internet. The routines are based on the method of lines (MOL), a general PDE algorithm that can be executed on modest computers within the basic R system. The reader can download and use the routines to confirm the model solutions reported in the book, then experiment with the model by varying the parameters and modifying/extending the equations, and even studying alternative models with the PDE methodology demonstrated by the CV-ICI model. Spatiotemporal Modeling of Cancer Immunotherapy: Partial Differential Equation Analysis in R facilitates the use of the model, and more generally, computer- based analysis of cancer immunotherapy mathematical models, as a step toward the development and quantitative evaluation of the immunotherapy approach to the treatment of cancer.
ISBN: 9783030190804$q(electronic bk.)
Standard No.: 10.1007/978-3-030-19080-4doiSubjects--Topical Terms:
841300
Cancer
--Immunotherapy
LC Class. No.: RC271.I45 / S354 2019
Dewey Class. No.: 616.99406
Spatiotemporal modeling of cancer immunotherapypartial differential equation analysis in R /
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Fixed Boundary PDE Model Formulation -- Fixed Boundary PDE Model Implementation -- Fixed Boundary PDE Model Output -- Moving Boundary PDE Model Implementation -- Moving Boundary PDE Model Output -- Index.
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The focus of this book is a detailed discussion of a dual cancer vaccine (CV)-immune checkpoint inhibitor (ICI) mathematical model formulated as a system of partial differential equations (PDEs) defining the spatiotemporal distribution of cells and biochemicals during tumor growth. A computer implementation of the model is discussed in detail for the quantitative evaluation of CV-ICI therapy. The coding (programming) consists of a series of routines in R, a quality, open-source scientific computing system that is readily available from the internet. The routines are based on the method of lines (MOL), a general PDE algorithm that can be executed on modest computers within the basic R system. The reader can download and use the routines to confirm the model solutions reported in the book, then experiment with the model by varying the parameters and modifying/extending the equations, and even studying alternative models with the PDE methodology demonstrated by the CV-ICI model. Spatiotemporal Modeling of Cancer Immunotherapy: Partial Differential Equation Analysis in R facilitates the use of the model, and more generally, computer- based analysis of cancer immunotherapy mathematical models, as a step toward the development and quantitative evaluation of the immunotherapy approach to the treatment of cancer.
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based on 0 review(s)
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1
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1圖書
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EB RC271.I45 S332 2019 2019
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1 records • Pages 1 •
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https://doi.org/10.1007/978-3-030-19080-4
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