Introduction to Modeling for Biosciences
Computational modeling has become an essential tool for researchers in the biological sciences. Yet in biological modeling, there is no one technique that is suitable for all problems. Instead, different problems call for different approaches. Furthermore
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David J. Barnes Dominique Chu
Introduction to Modeling for Biosciences
David J. Barnes Computing Laboratory University of Kent Canterbury, Kent CT2 7NF UK [email protected]
Dr. Dominique Chu Computing Laboratory University of Kent Canterbury, Kent CT2 7NF UK [email protected]
ISBN 978-1-84996-325-1 e-ISBN 978-1-84996-326-8 DOI 10.1007/978-1-84996-326-8 Springer London Dordrecht Heidelberg New York British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Control Number: 2010931520 © Springer-Verlag London Limited 2010 Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms of licenses issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers. The use of registered names, trademarks, etc., in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant laws and regulations and therefore free for general use. The publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made. Cover art by snailsnail Cover design: KünkelLopka GmbH, Heidelberg Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
David dedicates this book to Helen, Ben, (Hannah and John), John and Sarah
Preface
In this book we seek to provide a detailed introduction to a range of modeling techniques that are appropriate for modeling in biosciences. The book is primarily intended for bioscientists, but will be equally useful for anybody wishing to start modeling in biosciences and related fields. The topics we discuss include agentbased models, stochastic modeling techniques, differential equations and Gillespie’s stochastic simulation algorithm. Throughout, we pay particular attention to the needs of the novice modeler. We recognise that modeling in science in general (and in biology, in particular) requires both skills (i.e., programming, developing algorithms, and solving equations) and techniques (i.e., the ability to recognise what is important and needs to be represented in the model, and what can and should be left out). In our experience with novice modelers we have noticed that: (i) both skill and technique are equally important; and (ii) both are normally lacking to some degree. The philosophy of this book, therefore, is to discuss both aspects—the technical side, and the side that concerns being able to identify the right degree of abstraction. As far as the latter area is concerned, we do
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