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Recent developments have enhanced the applicability of normal mode analysis (NMA) to macromolecular assemblies, solid states, and non-linear spectroscopes. This book provides comprehensive coverage of molecular structure and dynamics and their implications for biological and chemical function.
Providing an overview of quantitative biology, this book presents practical tools for the observation, modeling, design, and manipulation of biological systems from the molecular to cellular levels. The book offers an introduction to fundamental concepts and computational, mathematical, and experimental studies of molecular and cellular behavior
This book introduces the emerging field of physical oncology, and includes recent breakthroughs in how novel mathematical models of physical transport processes incorporate patient tissue and imaging data routinely produced in the clinic to predict the efficacy of many cancer treatment approaches, including chemotherapy and radiation therapy.
Demonstrates the advantages and methods of obtaining exact solutions of the equations that describe nonlinear problems encountered in the study of invasive species spread. This work presents a collection of exactly solvable models. It provides insight into issues such as the impact of the Allee effect and the impact of predation.
Exactly Solvable Models of Biological Invasion demonstrates the advantages and methods of obtaining exact solutions of the equations that describe nonlinear problems encountered in the study of invasive species spread. The authors present a comprehensive collection of exactly solvable models and a unified, self-contained description of the relevant mathematical methods. They also provide new insight into important issues such as the impact of the Allee effect and the impact of predation. Full calculation details make this presentation accessible to biologists as well as applied mathematicians, and a range of ecological examples and applications demonstrate the utility of exact methods in practice.
Reviewing the significant progress made in understanding spatiotemporal patterning in ecological and epidemiological systems, this resource shows that mathematical modeling and numerical simulations are effective tools in the study of population ecology and epidemiology. It takes a unified approach to population dynamics and epidemiology by present
This book addresses mathematical models in the study of practical questions in ecology, particularly factors that affect herbivory. It will be of use for graduate students and researchers interested in mathematical biology and ecology.
Introduces the fundamental modeling and analytical techniques required to deepen understanding of biological phenomena. This text includes a section on spiral waves, developments in tumor biology, and covers the numerical solutions of different equations and numerical bifurcation analysis.
Cancer is a complex disease process that spans multiple scales in space and time. Drawing on an interdisciplinary group of distinguished international experts, this book discusses the scientific and technical expertise necessary to conduct innovative cancer modeling research across scales.
Develops the mathematical aspects of optimal control theory and provides insight into the application of this theory to biological models. This book examines the basic problem for continuous time ordinary differential equations (ODEs). It introduces the optimal control of discrete systems and of partial differential equations (PDEs).
There is a great deal of interest in population genetics in the applied probability and mathematical biology communities. This book provides an overview of applied probability methods in mathematical population genetics. It presents various techniques in a unified mathematical framework, covering evolutionary models, diffusion processes, coalescent theory, gene trees, ancestral inference and more. The methods are illustrated through real examples, and there are some exercises to enable the book to be used for teaching at graduate and postgraduate levels.
The extent and accessibility of modern sequencing technologies have transformed population genetics to population genomics. Focusing on this new area, this book explores the combination of combinatorial and statistical methods to produce novel algorithms to solve problems, bringing accuracy and efficiency simultaneously into the solution. Each chapter includes an explanation of the problem, the mathematical formulation, discussion of the theory, a list of exercises, references to further reading, and notes.
Extensively classroom-tested in undergraduate and graduate courses, this self-contained book presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases, modeling issues, and existing methods and their limitations. The authors introduce mathematical and programming tools, along with analytical and numerical studies of the models. They also develop new mathematical tools and look to future improvements on dynamical models.
This is one of the first books to provide a systematic study of the many stochastic models used in systems biology. The book shows how the mathematical models are used as technical tools for simulating biological processes and how the models lead to conceptual insights on the functioning of the cellular processing system. Examples cover the phage lambda genetic switch, eukaryotic gene expression, noise propagation in gene networks, and more. Most of the text should be accessible to scientists with basic knowledge in calculus and probability theory.
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