Modeling Biological Systems : Principles and Applications

James W. Haefner

ISBN 10: 1461368472 / ISBN 13: 9781461368472

Verlag: Springer US, Springer New York, 2012

Beschreibung

Druck auf Anfrage Neuware - Printed after ordering - This book is intended as a text for a first course on creating and analyzing computer simulation models of biological systems. The expected audience for this book are students wishing to use dynamic models to interpret real data mueh as they would use standard statistical techniques. It is meant to provide both the essential principles as well as the details and equa tions applicable to a few particular systems and subdisciplines. Biological systems, however, encompass a vast, diverse array of topics and problems. This book discusses only a select number of these that I have found to be useful and interesting to biologists just beginning their appreciation of computer simulation. The examples chosen span classical mathematical models of well-studied systems to state-of-the-art topics such as cellular automata and artificial life. I have stressed the relationship between the models and the biology over mathematical analysis in order to give the reader a sense that mathematical models really are useful to biologists. In this light, I have sought examples that address fundamental and, I think, interesting biological questions. Almost all of the models are directly COIIl pared to quantitative data to provide at least a partial demonstration that some biological models can accurately predict.

Bestandsnummer des Verkäufers 9781461368472

Bibliografische Details

• Titel: Modeling Biological Systems : Principles and Applications
• Verlag: Springer US, Springer New York
• Erscheinungsjahr: 2012
• Sprache: Englisch
• ISBN-10: 1461368472
• ISBN-13: 9781461368472
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 235B x 155 H x 27 T Millimeter Breite: 235 mm, Höhe: 155 mm, Tiefe: 27 mm
• Gewicht: 744 Gramm

Über diesen Titel

Inhaltsangabe

This book is intended as a text for a first course on creating and analyzing computer simulation models of biological systems. The expected audience for this book are students wishing to use dynamic models to interpret real data mueh as they would use standard statistical techniques. It is meant to provide both the essential principles as well as the details and equa­ tions applicable to a few particular systems and subdisciplines. Biological systems, however, encompass a vast, diverse array of topics and problems. This book discusses only a select number of these that I have found to be useful and interesting to biologists just beginning their appreciation of computer simulation. The examples chosen span classical mathematical models of well-studied systems to state-of-the-art topics such as cellular automata and artificial life. I have stressed the relationship between the models and the biology over mathematical analysis in order to give the reader a sense that mathematical models really are useful to biologists. In this light, I have sought examples that address fundamental and, I think, interesting biological questions. Almost all of the models are directly COIIl­ pared to quantitative data to provide at least a partial demonstration that some biological models can accurately predict.

Críticas

Throughout the book, the author aims to teach the concepts of mathematical modelling by example, allowing a full understanding of how and why mathematics is so important in biology. This is a superb introduction and complements the more technical literature... - The Biologist;
Covers a broad area with wit and enthusiasm, tempered with an appropriate degree of caution...a valuable introduction...a balanced selection of references makes this a handy source text for those seeking to learn more. - Journal of Animal Ecology;
The book will be useful for those readers who want to get a survey of the use of various types of models in biology. - Eur. Jnl. of Entomology, 1997;
This is an excellent book for the student who wants a mathematical model but does not know how to construct one - Journal of Experimental Marine Biology and Ecology.