Modeling And Differential Equations In Biology

Persistence in lotka-volterra models of food chains and competition; Mathematical models of humoral immune response; Mathematical models of dose and cell cycle effects in multifraction radiotherapy; Theorical and experimental investigations of microbial competition in continuous culture; A liapunov functional for a class of reaction-diffusion systems; Stochastic prey-predator relationships; Coexistence in predator-prey systems; Stability of some multispecies population models; Population dynamics in patchy environments; Limit cycles in a model of b-cell simulation; Optimal age-specific harvesting policy for a cintinuous time-population model; Models involving differential and integral equations appropriate for describing a temperature dependent predator-prey mite ecosystem on apples.

Based on a very successful one-semester course taught at Harvard, this text teaches students in the life sciences how to use differential equations to help their research. It needs only a semester's background in calculus. Ideas from linear algebra and partial differential equations that are most useful to the life sciences are introduced as needed, and in the context of life science applications, are drawn from real, published papers. It also teaches students how to recognize when differential equations can help focus research. A course taught with this book can replace the standard course in multivariable calculus that is more usually suited to engineers and physicists.

First published in 1980. CRC Press is an imprint of Taylor & Francis.

Deepen students' understanding of biological phenomenaSuitable for courses on differential equations with applications to mathematical biology or as an introduction to mathematical biology, Differential Equations and Mathematical Biology, Second Edition introduces students in the physical, mathematical, and biological sciences to fundamental modeli

Given that a college level life science student will take only one additional calculus course after learning its very basics, what material should such a course cover? This book answers that question. It is based on a very successful one-semester course taught at Harvard and aims to teach students in the life sciences understanding the use of differential equations. It is enriched with illustrative examples from real papers. Necessary notions from linear algebra and partial differential equations are introduced as and when needed, and in the context of applications. Drawing on a very successful one-semester course at Harvard, this text aims to teach students in the life sciences how to use differential equations. It is enriched with illustrative examples from real papers. Necessary notions from mathematics are introduced as and when needed, and in the context of applications. Aimed at biologists wishing to understand mathematical modelling rather than just learning math methods.

How do biological objects communicate, make structures, make measurements and decisions, search for food, i.e., do all the things necessary for survival? Designed for an advanced undergraduate audience, this book uses mathematics to begin to tell that story. It builds on a background in multivariable calculus, ordinary differential equations, and basic stochastic processes and uses partial differential equations as the framework within which to explore these questions.

This book on mathematical modeling of biological processes includes a wide selection of biological topics that demonstrate the power of mathematics and computational codes in setting up biological processes with a rigorous and predictive framework. Topics include: enzyme dynamics, spread of disease, harvesting bacteria, competition among live species, neuronal oscillations, transport of neurofilaments in axon, cancer and cancer therapy, and granulomas. Complete with a description of the biological background and biological question that requires the use of mathematics, this book is developed for graduate students and advanced undergraduate students with only basic knowledge of ordinary differential equations and partial differential equations; background in biology is not required. Students will gain knowledge on how to program with MATLAB without previous programming experience and how to use codes in order to test biological hypothesis.

This book is based on a one semester course that the authors have been teaching for several years, and includes two sets of case studies. The first includes chemostat models, predator-prey interaction, competition among species, the spread of infectious diseases, and oscillations arising from bifurcations. In developing these topics, readers will also be introduced to the basic theory of ordinary differential equations, and how to work with MATLAB without having any prior programming experience. The second set of case studies were adapted from recent and current research papers to the level of the students. Topics have been selected based on public health interest. This includes the risk of atherosclerosis associated with high cholesterol levels, cancer and immune interactions, cancer therapy, and tuberculosis. Readers will experience how mathematical models and their numerical simulations can provide explanations that guide biological and biomedical research. Considered to be the undergraduate companion to the more advanced book "Mathematical Modeling of Biological Processes" (A. Friedman, C.-Y. Kao, Springer – 2014), this book is geared towards undergraduate students with little background in mathematics and no biological background.