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# Dynamics of Cancer

Mathematical Foundations of Oncology

## Overview

The book aims to provide an introduction to mathematical models that describe the dynamics of tumor growth and the evolution of tumor cells. It can be used as a textbook for advanced undergraduate or graduate courses, and also serves as a reference book for researchers. The book has a strong evolutionary component and reflects the viewpoint that cancer can be understood rationally through a combination of mathematical and biological tools. It can be used both by mathematicians and biologists. Mathematically, the book starts with relatively simple ordinary differential equation models, and subsequently explores more complex stochastic and spatial models. Biologically, the book starts with explorations of the basic dynamics of tumor growth, including competitive interactions among cells, and subsequently moves on to the evolutionary dynamics of cancer cells, including scenarios of cancer initiation, progression, and treatment. The book finishes with a discussion of advanced topics, which describe how some of the mathematical concepts can be used to gain insights into a variety of questions, such as epigenetics, telomeres, gene therapy, and social interactions of cancer cells.

Principles of Economics (Illustrated)

The book has an active table of contents for readers to access each chapter. Principles of Economics by Frank A. Fetter constructed a general theory of economics in the Austrian tradition. Using the axiomatic-deductive method, Fetter traced economic laws to individual human action. The book also demonstrated that the rate of interest…

Contents:
• Teaching Guide
• Cancer and Somatic Evolution
• Mathematical Modeling of Tumorigenesis
• Basic Growth Dynamics and Deterministic Models:
• Single Species Growth
• Two-Species Competition Dynamics
• Competition Between Genetically Stable and Unstable Cells
• Chromosomal Instability and Tumor Growth
• Angiogenesis Inhibitors, Promoters, and Spatial Growth
• Evolutionary Dynamics and Stochastic Models:
• Evolutionary Dynamics of Tumor Initiation Through Oncogenes: The Gain-of-Function Model
• Evolutionary Dynamics of Tumor Initiation Through Tumor-Suppressor Genes: The Loss-of-Function Model and Stochastic Tunneling
• Microsatellite and Chromosomal Instability in Sporadic and Familial Colorectal Cancers
• Evolutionary Dynamics in Hierarchical Populations
• Spatial Evolutionary Dynamics of Tumor Initiation
• Complex Tumor Dynamics in Space
• Stochastic Modeling of Cellular Growth, Treatment, and Resistance Generation
• Evolutionary Dynamics of Drug Resistance in Chronic Myeloid Leukemia
• Evolutionary Dynamics of Stem-Cell Driven Tumor Growth
• Tumor Growth Kinetics and Disease Progression
• Epigenetic Changes and the Rate of DNA Methylation
• Telomeres and Cancer Protection
• Gene Therapy and Oncolytic Virus Therapy
• Immune Responses,Tumor Growth, and Therapies
• Towards Higher Complexities: Social Interactions

Readership: Researchers in mathematical biology, mathematical modeling, biology, mathematical oncology.

Date release: April 24, 2014

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