Handbook of Statistical Bioinformatics
Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and appropriate tools in computational statistics integrated with biological knowledge and
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For further volumes: http://www.springer.com/series/7286
Henry Horng-Shing Lu Hongyu Zhao
Bernhard Sch¨olkopf
Editors
Handbook of Statistical Bioinformatics
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Editors Henry Horng-Shing Lu National Chiao Tung University Institute of Statistics 1001 Ta Hsueh Road 30010 Hsinchu Taiwan R.O.C. [email protected] http://www.stat.nctu.edu.tw/misg/eindex.htm
Bernhard Sch¨olkopf MPI for Intelligent Systems Department of Empirical Inference Spemanstr. 38 72076 T¨ubingen Germany [email protected] http://www.tuebingen.mpg.de/bs
Hongyu Zhao Yale University School of Medicine Dept. Epidemiology and Public Health College Street 60 New Haven, 06520 CT USA [email protected] http://bioinformatics.med.yale.edu/group/
ISBN 978-3-642-16344-9 e-ISBN 978-3-642-16345-6 DOI 10.1007/978-3-642-16345-6 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2011928711 c Springer-Verlag Berlin Heidelberg 2011 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, 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 protective laws and regulations and therefore free for general use. Cover design: deblik, Berlin Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Foreword
Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that reveal different aspects of biological processes at the whole genome level. However, these data are highly complex and demand the development of sophisticated statistical tools, integrated with biological knowledge and implemented as computational algorithms. This volume collects a number of statistical developments from leading researchers to survey the many active research topics in computational biology and promote the visibility of this fast evolving research area. Introductory background material can be found in books on computational statistics, such as the Springer handbook edited by Gentle et al. (2004). The present book aims to serve as an introduction and reference on statistical methods in computational biology. It addresses students and researchers in statistics, computer science, and biological and biomedical research. We hope that most of the common topics in the field are covered in this book, and that its publication will further bridge computational statistics
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