Introduction.- Statistics: The Backgrounds & The Basis.- Attacker & Defender Model: The Dynamics of the Immune System.- Mathematical Modeling of Metastatic Cancer.- Mathematical/Computational Modeling of Advanced Immunotherapy.- Mathematical Modeling & Computational Studies On The War Against Breast Cancer.- Gene Therapy.- The Smartest Fighters.- Nutritional Therapy.- The Fateful Code & The Future Course.- Conclusion.
SUHRIT KUMAR DEY is Professor Emeritus in the Department of Mathematics and Computer Science, Eastern Illinois University, USA. He has developed a perturbed functional iteration to solve nonlinear models and a time-varying matrix, known as D-matrix, which monitors numerical stability of a nonlinear model as computational schemes go to convergence. He has delivered several invited talks on these topics at many international conferences and universities including Harvard University, Yale University, Stanford University, and NASA Ames Research Centre at the University of Cambridge, USA. As Author of over 60 publications, he is Member of various professional societies.
CHARLIE DEY is Director of Training and Professional Development in the User Services Group at Texas Advanced Computing Center (TACC) with a background in Web development and scientific computing. Prior to joining TACC, he worked as Senior Application Developer for the Carle Foundation and as Computer Science Instructor at Parkland College in Champaign, Illinois, USA. He holds a bachelor's degree in computer science and biology from Eastern Illinois University and certifications in 3D programing and visualization. He was also Member of a specialized application development team at the University of Illinois and has been a contracted research consultant for NASA Ames Research Center, studying computational immunology and bioinformatics. His research works are published in various journals of repute. Bioinformatics, numerical analysis, object-oriented programming, parallel programming, and computer animation are some of his professional interests.
This book’s aim is to study the mathematical and computational models to analyze the progress, prognosis, prevention, and panacea of breast cancer. The book discusses application of Markov chains and transient mappings, Charlie–Simpson numerical algorithm, models represented by nonlinear reaction–diffusion-type partial differential equations, and related techniques. The book also attempts to design mathematical model of targeted strategic treatments by using Skilled Killer Drugs (SKD1 and SKD2) to suggest the improvisation of future cancer treatments. Both graduate students and researchers of computational biology and oncologists will benefit by studying this book. Researchers of cancer studies and biological sciences will also find this work helpful.