Problem Solving Handbook in Computational Biology and Bioinformatics
Bioinformatics is growing by leaps and bounds; theories/algorithms/statistical techniques are constantly evolving. Nevertheless, a core body of algorithmic ideas have emerged and researchers are beginning to adopt a "problem solving" approach to bioinform
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Lenwood S. Heath • Naren Ramakrishnan Editors
Problem Solving Handbook in Computational Biology and Bioinformatics
Editors Lenwood S. Heath Department of Computer Science Virginia Tech 114 McBryde Hall 24061-0106 Blacksburg Virginia USA [email protected]
Naren Ramakrishnan Department of Computer Science Virginia Tech 114 McBryde Hall 24061-0106 Blacksburg Virginia USA [email protected]
ISBN 978-0-387-09759-6 e-ISBN 978-0-387-09760-2 DOI 10.1007/978-0-387-09760-2 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2010938722 © Springer Science+Business Media, LLC 2011 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
LSH acknowledges the loving support of Deanie, James, and Kaitlin, who are always his inspiration. NR dedicates this book to Kayar and Anant for their unwavering love.
Preface
Bioinformatics is today a breadth-wise subject spanning practically every aspect of the life sciences, from studying DNA sequences, to modeling the structure and function of proteins, to unraveling the interactions between proteins, and finally to capturing the relationship with phenotypes of organisms. While there are several excellent textbooks and monographs covering every aspect of the field, there is a need to collect together, in one place, the algorithms and methods that form the modern bioinformatician’s toolkit. The Problem Solving Handbook in Computational Biology and Bioinformatics was conceived to fill this need. In organizing this book, we have consciously chosen those topics that have strong algorithmic or methodological underpinnings and that are now widely used in a range of bioinformatics investigations, such as functional genomics, haplotype studies, and simulation of disease pathways. The intended audience for this book are practitioners of bioinformatics algorithms. The coverage is not (intended to be) exhaustive. The chapters are written by experts in their respective disciplines and are closely organized with an introduction to the underlying problem/task/domain, detailed algorithmic descriptions, available software implementations, applications, and advanced topics. For the benefit of the reader, exercises and references to the literature for further reading are also provided. The five sections of the handbook fo
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