Bioinformatics Methods in Clinical Research
Integrated bioinformatics solutions have become increasingly valuable in past years, as technological advances have allowed researchers to consider the potential of omics for clinical diagnosis, prognosis, and therapeutic purposes, and as the costs of suc
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MO L E C U L A R BI O L O G Y
Series Editor John M. Walker School of Life Sciences University of Hertfordshire Hatfield, Hertfordshire, AL10 9AB, UK
For other titles published in this series, go to www.springer.com/series/7651
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Bioinformatics Methods in Clinical Research Edited by
Rune Matthiesen Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), University of Porto, Porto, Portugal
Editor Rune Matthiesen Universidade do Porto Inst. Patologia e Imunologia Molecular (IPATIMUP) Rua Dr. Roberto Frias s/n 4200-465 Porto Portugal [email protected]
ISSN 1064-3745 e-ISSN 1940-6029 ISBN 978-1-60327-193-6 e-ISBN 978-1-60327-194-3 DOI 10.1007/978-1-60327-194-3 Library of Congress Control Number: 2009939536 © Humana Press, a part of Springer Science+Business Media, LLC 2010 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Humana Press, c/o 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.com
Preface This book discusses the latest developments in clinical omics research and describes in detail a subset of the algorithms used in publicly available software tools. The book should be considered as an omics-bioinformatics resource. However, it is not just a pure bioinformatics resource filled with complex equations; it describes to some extent the biological background and also discusses experimental methods. The advantages and drawbacks of the various experimental methods in relation to data analysis will be reviewed as well. In other words, the intention is to establish a bridge between theory and practice. Practical examples showing methods, results, and conclusions from data mining strategies will be given in some cases. It is not possible to cover all areas of omics techniques and bioinformatics algorithms in one book. However, an important subset is described and discussed from both the experimental and the bioinformatics views. The book starts out by discussing various successful examples in which omics techniques have been used in a clinically related study. An important buzz word in omics is biomarkers. The word “biomarker” has different meanings depending on the context in which it is used. Here, it is used in a clinical context and should be interpreted as “a substance whose specific level indicates a particular cellular or clinical state.” In theory, one could easily imagine cases where one biomarker is fou
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