Algebraic and Numeric Biology

Algebraic and Numeric Biology
Author: Katsuhisa Horimoto
Publisher: Springer Science & Business Media
Total Pages: 193
Release: 2012-02-14
Genre: Computers
ISBN: 3642280668

This book constitutes the refereed proceedings of the 4th International Conference on Algebraic Biology, ANB 2010, held at the Castle of Hagenberg, Austria in July/August 2010. The conference is a follow up of the AB Conference. The 10 papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on mathematical modeling, system analysis and design, genomics, molecular structure analysis, automata theory, artificial intelligence, sequence analysis, automated reasoning, formal language and hybrid symbolic numerical methods.

A Course in Mathematical Biology

A Course in Mathematical Biology
Author: Gerda de Vries
Publisher: SIAM
Total Pages: 307
Release: 2006-07-01
Genre: Mathematics
ISBN: 0898718252

This is the only book that teaches all aspects of modern mathematical modeling and that is specifically designed to introduce undergraduate students to problem solving in the context of biology. Included is an integrated package of theoretical modeling and analysis tools, computational modeling techniques, and parameter estimation and model validation methods, with a focus on integrating analytical and computational tools in the modeling of biological processes. Divided into three parts, it covers basic analytical modeling techniques; introduces computational tools used in the modeling of biological problems; and includes various problems from epidemiology, ecology, and physiology. All chapters include realistic biological examples, including many exercises related to biological questions. In addition, 25 open-ended research projects are provided, suitable for students. An accompanying Web site contains solutions and a tutorial for the implementation of the computational modeling techniques. Calculations can be done in modern computing languages such as Maple, Mathematica, and MATLAB?.

Mathematical Models in Biology

Mathematical Models in Biology
Author: Leah Edelstein-Keshet
Publisher: SIAM
Total Pages: 629
Release: 1988-01-01
Genre: Mathematics
ISBN: 9780898719147

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.

Algebraic Statistics for Computational Biology

Algebraic Statistics for Computational Biology
Author: L. Pachter
Publisher: Cambridge University Press
Total Pages: 440
Release: 2005-08-22
Genre: Mathematics
ISBN: 9780521857000

This book, first published in 2005, offers an introduction to the application of algebraic statistics to computational biology.

Biology by Numbers

Biology by Numbers
Author: Richard F. Burton
Publisher: Cambridge University Press
Total Pages: 260
Release: 1998-02-26
Genre: Mathematics
ISBN: 9780521576987

A practical undergraduate textbook for maths-shy biology students showing how basic maths reveals important insights.

Quantifying Life

Quantifying Life
Author: Dmitry A. Kondrashov
Publisher: University of Chicago Press
Total Pages: 434
Release: 2016-08-04
Genre: Science
ISBN: 022637193X

Since the time of Isaac Newton, physicists have used mathematics to describe the behavior of matter of all sizes, from subatomic particles to galaxies. In the past three decades, as advances in molecular biology have produced an avalanche of data, computational and mathematical techniques have also become necessary tools in the arsenal of biologists. But while quantitative approaches are now providing fundamental insights into biological systems, the college curriculum for biologists has not caught up, and most biology majors are never exposed to the computational and probabilistic mathematical approaches that dominate in biological research. With Quantifying Life, Dmitry A. Kondrashov offers an accessible introduction to the breadth of mathematical modeling used in biology today. Assuming only a foundation in high school mathematics, Quantifying Life takes an innovative computational approach to developing mathematical skills and intuition. Through lessons illustrated with copious examples, mathematical and programming exercises, literature discussion questions, and computational projects of various degrees of difficulty, students build and analyze models based on current research papers and learn to implement them in the R programming language. This interplay of mathematical ideas, systematically developed programming skills, and a broad selection of biological research topics makes Quantifying Life an invaluable guide for seasoned life scientists and the next generation of biologists alike.

Mathematical Methods in Biology

Mathematical Methods in Biology
Author: J. David Logan
Publisher: John Wiley & Sons
Total Pages: 437
Release: 2009-08-17
Genre: Science
ISBN: 0470525878

A one-of-a-kind guide to using deterministic and probabilistic methods for solving problems in the biological sciences Highlighting the growing relevance of quantitative techniques in scientific research, Mathematical Methods in Biology provides an accessible presentation of the broad range of important mathematical methods for solving problems in the biological sciences. The book reveals the growing connections between mathematics and biology through clear explanations and specific, interesting problems from areas such as population dynamics, foraging theory, and life history theory. The authors begin with an introduction and review of mathematical tools that are employed in subsequent chapters, including biological modeling, calculus, differential equations, dimensionless variables, and descriptive statistics. The following chapters examine standard discrete and continuous models using matrix algebra as well as difference and differential equations. Finally, the book outlines probability, statistics, and stochastic methods as well as material on bootstrapping and stochastic differential equations, which is a unique approach that is not offered in other literature on the topic. In order to demonstrate the application of mathematical methods to the biological sciences, the authors provide focused examples from the field of theoretical ecology, which serve as an accessible context for study while also demonstrating mathematical skills that are applicable to many other areas in the life sciences. The book's algorithms are illustrated using MATLAB®, but can also be replicated using other software packages, including R, Mathematica®, and Maple; however, the text does not require any single computer algebra package. Each chapter contains numerous exercises and problems that range in difficulty, from the basic to more challenging, to assist readers with building their problem-solving skills. Selected solutions are included at the back of the book, and a related Web site features supplemental material for further study. Extensively class-tested to ensure an easy-to-follow format, Mathematical Methods in Biology is an excellent book for mathematics and biology courses at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals working in the fields of biology, ecology, and biomathematics.

Introduction to Mathematical Biology

Introduction to Mathematical Biology
Author: Ching Shan Chou
Publisher: Springer
Total Pages: 174
Release: 2016-04-27
Genre: Mathematics
ISBN: 3319296388

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.

A Primer in Mathematical Models in Biology

A Primer in Mathematical Models in Biology
Author: Lee A. Segel
Publisher: SIAM
Total Pages: 435
Release: 2013-05-09
Genre: Science
ISBN: 1611972493

A textbook on mathematical modelling techniques with powerful applications to biology, combining theoretical exposition with exercises and examples.

Computational Methods in Cell Biology

Computational Methods in Cell Biology
Author: Anand R. Asthagiri
Publisher: Academic Press
Total Pages: 427
Release: 2012-04-13
Genre: Computers
ISBN: 0123884039

Computational methods are playing an ever increasing role in cell biology. This volume of Methods in Cell Biology focuses on Computational Methods in Cell Biology and consists of two parts: (1) data extraction and analysis to distill models and mechanisms, and (2) developing and simulating models to make predictions and testable hypotheses. Focuses on computational methods in cell biology Split into 2 parts--data extraction and analysis to distill models and mechanisms, and developing and simulating models to make predictions and testable hypotheses Emphasizes the intimate and necessary connection with interpreting experimental data and proposing the next hypothesis and experiment