Multiscale modeling of cancer : an integrated experimental and mathematical modeling approach

Description

The correct functioning of the mammalian brain depends on the integrated activity of myriad neuronal and non-neuronal cells. Discrete areas serve discrete functions, and dispersed or distributed communities of cells serve others. Throughout, these networks of activity are under the control of neuromodulatory systems. One goal of current neuroscientific research is to elucidate the precise methods by which these systems operate, especially during normal conscious behaviours and processes. Mircea Steriade and Denis Paré describe the neuronal properties and networks that exist within and between the cortex and two important sub-cortical structures: the thalamus and amygdala. The authors explore the changes in these properties, covering topics including morphology, electrophysiology, architecture and gating; and comparing regions and systems in both normal and diseased states. Aimed at graduates and postdoctoral researchers in neuroscience "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"--Provided by publisher.  Read more... Machine generated contents note: 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