Biology in Time and Space

Biology in Time and Space PDF Author: James P. Keener
Publisher:
ISBN: 9781470464141
Category : Biomathematics
Languages : en
Pages :

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Book Description

Biology in Time and Space

Biology in Time and Space PDF Author: James P. Keener
Publisher:
ISBN: 9781470464141
Category : Biomathematics
Languages : en
Pages :

Get Book Here

Book Description


Biology in Time and Space: A Partial Differential Equation Modeling Approach

Biology in Time and Space: A Partial Differential Equation Modeling Approach PDF Author: James P. Keener
Publisher: American Mathematical Soc.
ISBN: 1470454289
Category : Education
Languages : en
Pages : 326

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Book Description
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.

Methods of Small Parameter in Mathematical Biology

Methods of Small Parameter in Mathematical Biology PDF Author: Jacek Banasiak
Publisher: Springer Science & Business
ISBN: 3319051407
Category : Mathematics
Languages : en
Pages : 295

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Book Description
This monograph presents new tools for modeling multiscale biological processes. Natural processes are usually driven by mechanisms widely differing from each other in the time or space scale at which they operate and thus should be described by appropriate multiscale models. However, looking at all such scales simultaneously is often infeasible, costly, and provides information that is redundant for a particular application. Hence, there has been a growing interest in providing a more focused description of multiscale processes by aggregating variables in a way that is relevant to the purpose at hand and preserves the salient features of the dynamics. Many ad hoc methods have been devised, and the aim of this book is to present a systematic way of deriving the so-called limit equations for such aggregated variables and ensuring that the coefficients of these equations encapsulate the relevant information from the discarded levels of description. Since any approximation is only valid if an estimate of the incurred error is available, the tools the authors describe allow for proving that the solutions to the original multiscale family of equations converge to the solution of the limit equation if the relevant parameter converges to its critical value. The chapters are arranged according to the mathematical complexity of the analysis, from systems of ordinary linear differential equations, through nonlinear ordinary differential equations, to linear and nonlinear partial differential equations. Many chapters begin with a survey of mathematical techniques needed for the analysis. All problems discussed in this book belong to the class of singularly perturbed problems; that is, problems in which the structure of the limit equation is significantly different from that of the multiscale model. Such problems appear in all areas of science and can be attacked using many techniques. Methods of Small Parameter in Mathematical Biology will appeal to senior undergraduate and graduate students in applied and biomathematics, as well as researchers specializing in differential equations and asymptotic analysis.

Mathematical Models in Biology

Mathematical Models in Biology PDF Author: Leah Edelstein-Keshet
Publisher: SIAM
ISBN: 9780898719147
Category : Mathematics
Languages : en
Pages : 629

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Book Description
Mathematical Models in Biology is an introductory book for readers interested in biological applications of mathematics and modeling in biology. A favorite in the mathematical biology community, it shows how relatively simple mathematics can be applied to a variety of models to draw interesting conclusions. Connections are made between diverse biological examples linked by common mathematical themes. A variety of discrete and continuous ordinary and partial differential equation models are explored. Although great advances have taken place in many of the topics covered, the simple lessons contained in this book are still important and informative. Audience: the book does not assume too much background knowledge--essentially some calculus and high-school algebra. It was originally written with third- and fourth-year undergraduate mathematical-biology majors in mind; however, it was picked up by beginning graduate students as well as researchers in math (and some in biology) who wanted to learn about this field.

Introduction to Partial Differential Equations

Introduction to Partial Differential Equations PDF Author: Peter J. Olver
Publisher: Springer Science & Business Media
ISBN: 3319020994
Category : Mathematics
Languages : en
Pages : 636

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Book Description
This textbook is designed for a one year course covering the fundamentals of partial differential equations, geared towards advanced undergraduates and beginning graduate students in mathematics, science, engineering, and elsewhere. The exposition carefully balances solution techniques, mathematical rigor, and significant applications, all illustrated by numerous examples. Extensive exercise sets appear at the end of almost every subsection, and include straightforward computational problems to develop and reinforce new techniques and results, details on theoretical developments and proofs, challenging projects both computational and conceptual, and supplementary material that motivates the student to delve further into the subject. No previous experience with the subject of partial differential equations or Fourier theory is assumed, the main prerequisites being undergraduate calculus, both one- and multi-variable, ordinary differential equations, and basic linear algebra. While the classical topics of separation of variables, Fourier analysis, boundary value problems, Green's functions, and special functions continue to form the core of an introductory course, the inclusion of nonlinear equations, shock wave dynamics, symmetry and similarity, the Maximum Principle, financial models, dispersion and solutions, Huygens' Principle, quantum mechanical systems, and more make this text well attuned to recent developments and trends in this active field of contemporary research. Numerical approximation schemes are an important component of any introductory course, and the text covers the two most basic approaches: finite differences and finite elements.

Exploring Modeling with Data and Differential Equations Using R

Exploring Modeling with Data and Differential Equations Using R PDF Author: John Zobitz
Publisher: CRC Press
ISBN: 1000776786
Category : Mathematics
Languages : en
Pages : 362

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Book Description
Exploring Modeling with Data and Differential Equations Using R provides a unique introduction to differential equations with applications to the biological and other natural sciences. Additionally, model parameterization and simulation of stochastic differential equations are explored, providing additional tools for model analysis and evaluation. This unified framework sits "at the intersection" of different mathematical subject areas, data science, statistics, and the natural sciences. The text throughout emphasizes data science workflows using the R statistical software program and the tidyverse constellation of packages. Only knowledge of calculus is needed; the text’s integrated framework is a stepping stone for further advanced study in mathematics or as a comprehensive introduction to modeling for quantitative natural scientists. The text will introduce you to: modeling with systems of differential equations and developing analytical, computational, and visual solution techniques. the R programming language, the tidyverse syntax, and developing data science workflows. qualitative techniques to analyze a system of differential equations. data assimilation techniques (simple linear regression, likelihood or cost functions, and Markov Chain, Monte Carlo Parameter Estimation) to parameterize models from data. simulating and evaluating outputs for stochastic differential equation models. An associated R package provides a framework for computation and visualization of results. It can be found here: https://cran.r-project.org/web/packages/demodelr/index.html.

Partial Differential Equations in Action

Partial Differential Equations in Action PDF Author: Sandro Salsa
Publisher: Springer
ISBN: 3319150936
Category : Mathematics
Languages : en
Pages : 714

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Book Description
The book is intended as an advanced undergraduate or first-year graduate course for students from various disciplines, including applied mathematics, physics and engineering. It has evolved from courses offered on partial differential equations (PDEs) over the last several years at the Politecnico di Milano. These courses had a twofold purpose: on the one hand, to teach students to appreciate the interplay between theory and modeling in problems arising in the applied sciences, and on the other to provide them with a solid theoretical background in numerical methods, such as finite elements. Accordingly, this textbook is divided into two parts. The first part, chapters 2 to 5, is more elementary in nature and focuses on developing and studying basic problems from the macro-areas of diffusion, propagation and transport, waves and vibrations. In turn the second part, chapters 6 to 11, concentrates on the development of Hilbert spaces methods for the variational formulation and the analysis of (mainly) linear boundary and initial-boundary value problems.

The Restless Cell

The Restless Cell PDF Author: Christina Hueschen
Publisher: Princeton University Press
ISBN: 0691236372
Category : Science
Languages : en
Pages : 437

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Book Description
An essential introduction to the physics of active matter and its application to questions in biology In recent decades, the theory of active matter has emerged as a powerful tool for exploring the differences between living and nonliving states of matter. The Restless Cell provides a self-contained, quantitative description of how the continuum theory of matter has been generalized to account for the complex and sometimes counterintuitive behaviors of living materials. Christina Hueschen and Rob Phillips begin by illustrating how classical field theory has been used by physicists to describe the transport of matter by diffusion, the elastic deformations of solids, and the flow of fluids. Drawing on physical insights from the study of diffusion, they introduce readers to the continuum theory protocol—a step-by-step framework for developing equations that describe matter as a continuum—and show how these methods and concepts can be generalized to the study of living, energy-consuming matter. Hueschen and Phillips then present a range of engaging biological case studies across scales, such as the symmetry breaking that occurs in developing embryos, the perpetual flows that take place in giant algal cells, and the herding of wildebeest on the plains of the Serengeti. An essential resource for students and researchers in biological physics and quantitative biology, The Restless Cell gives complete derivations of all calculations and features illustrations by Nigel Orme that seamlessly bridge conceptual models and continuum descriptions of living matter.

Modeling Life

Modeling Life PDF Author: Alan Garfinkel
Publisher: Springer
ISBN: 3319597310
Category : Mathematics
Languages : en
Pages : 456

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Book Description
This book develops the mathematical tools essential for students in the life sciences to describe interacting systems and predict their behavior. From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. Complex feedback relations and counter-intuitive responses are common in nature; this book develops the quantitative skills needed to explore these interactions. Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler’s method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models throughout. Encountering these concepts in context, students learn not only quantitative techniques, but how to bridge between biological and mathematical ways of thinking. Examples range broadly, exploring the dynamics of neurons and the immune system, through to population dynamics and the Google PageRank algorithm. Each scenario relies only on an interest in the natural world; no biological expertise is assumed of student or instructor. Building on a single prerequisite of Precalculus, the book suits a two-quarter sequence for first or second year undergraduates, and meets the mathematical requirements of medical school entry. The later material provides opportunities for more advanced students in both mathematics and life sciences to revisit theoretical knowledge in a rich, real-world framework. In all cases, the focus is clear: how does the math help us understand the science?

Introduction to Partial Differential Equations

Introduction to Partial Differential Equations PDF Author: Aslak Tveito
Publisher: Springer Science & Business Media
ISBN: 0387227733
Category : Mathematics
Languages : en
Pages : 402

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Book Description
Combining both the classical theory and numerical techniques for partial differential equations, this thoroughly modern approach shows the significance of computations in PDEs and illustrates the strong interaction between mathematical theory and the development of numerical methods. Great care has been taken throughout the book to seek a sound balance between these techniques. The authors present the material at an easy pace and exercises ranging from the straightforward to the challenging have been included. In addition there are some "projects" suggested, either to refresh the students memory of results needed in this course, or to extend the theories developed in the text. Suitable for undergraduate and graduate students in mathematics and engineering.