Articoli correlati a Selected Topics in Cancer Modeling
Sinossi
This collection of selected chapters offers a comprehensive overview of state-of-the-art mathematical methods and tools for modeling and analyzing cancer phenomena. Topics covered include stochastic evolutionary models of cancer initiation and progression, tumor cords and their response to anticancer agents, and immune competition in tumor progression and prevention. The complexity of modeling living matter requires the development of new mathematical methods and ideas. This volume, written by first-rate researchers in the field of mathematical biology, is one of the first steps in that direction.
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From the Back Cover
A major challenge in the modeling and simulation of tumor growth is the mathematical description of living matter, which is far more complex than a mathematical description of inert matter. One critical piece of this challenge is creating multiscale models that take into account subcellular, cellular, and macroscopic levels of cancer. The complexity of these different levels requires the development of new mathematical methods and ideas, which are examined in this work.
Written by first-rate researchers in the field of mathematical biology, this collection of selected chapters offers a comprehensive overview of state-of-the-art mathematical methods and tools for modeling and analyzing cancer phenomena.
Topics covered include:
* Genetic and epigenetic pathways to colon cancer
* A game theoretical perspective on the somatic evolution of cancer
* Nonlinear modeling and simulation of tumor growth
* Tumor cords and their response to anticancer agents
* Modeling diffusely invading brain tumors
* Multiphase models of tumor growth
* Mathematical modeling of breast carcinogenesis
* Predictive models in tumor immunology
* Multiscale modeling of solid tumor growth
Selected Topics in Cancer Modeling is an excellent reference for researchers, practitioners, and graduate students in applied mathematics, mathematical biology, and related fields. The book has an overall aim of quantitative, predictive mathematical modeling of solid tumor growth at all scales, from genetics all the way through to treatment therapy for patients.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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