Multiscale Modeling of Cancer
An Integrated Experimental and Mathematical Modeling Approach
$181.00 ( ) USD
- Authors:
- Vittorio Cristini, University of Texas Health Science Center, Houston
- John Lowengrub, University of California, Irvine
- Date Published: August 2010
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
- format: Adobe eBook Reader
- isbn: 9780511796142
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Mathematical modeling, analysis and simulation are set to play crucial roles in explaining tumor behavior, and the uncontrolled growth of cancer cells over multiple time and spatial scales. This book, the first to integrate state-of-the-art numerical techniques with experimental data, provides an in-depth assessment of tumor cell modeling at multiple scales. The first part of the text presents a detailed biological background with an examination of single-phase and multi-phase continuum tumor modeling, discrete cell modeling, and hybrid continuum-discrete modeling. In the final two chapters, the authors guide the reader through problem-based illustrations and case studies of brain and breast cancer, to demonstrate the future potential of modeling in cancer research. This book has wide interdisciplinary appeal and is a valuable resource for mathematical biologists, biomedical engineers and clinical cancer research communities wishing to understand this emerging field.
Read more- Provides a uniquely multidisciplinary approach to cancer research by combining state-of-the-art mathematical models with experimental data
- Includes case studies of brain and breast cancer to aid understanding and illustrate the potential of computational techniques in cancer research
- Helps researchers identify new directions of research in oncology
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×Product details
- Date Published: August 2010
- format: Adobe eBook Reader
- isbn: 9780511796142
- contains: 55 b/w illus. 5 tables
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
Part I. Theory:
1. Introduction
2. Biological background
3. Continuum tumor modeling: single phase
4. Analysis and calibration of single-phase continuum tumor models
5. Continuum tumor modeling: multiphase
6. Discrete cell modeling
7. Hybrid continuum-discrete models
8. Numerical schemes
Part II. Applications:
9. Continuum tumor modeling: a multidisciplinary approach
10. Agent-based cell modeling: application to breast cancer.-
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