Data Mining in Bioinformatics [Wang, Zaki, Tolvonen & Shasha 2004-09-17].pdf

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Advanced Information and Knowledge Processing
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Jason T.L. Wang, Mohammed J. Zaki,
Hannu T.T. Toivonen and Dennis Shasha
(Eds)
Data Mining in
Bioinformatics
With
110
Figures
Jason T.L. Wang, PhD
New Jersey Institute of Technology, USA
Mohammed J. Zaki, PhD
Computer Science Department, Rensselaer Polytechnic Institute, USA
Hannu T.T. Toivonen, PhD
University of Helsinki and Nokia Research Center
Dennis Shasha, PhD
New York University, USA
Series Editors
Xindong Wu
Lakhmi Jain
British Library Cataloguing in Publication Data
Data mining in bioinformatics. — (Advanced information and
knowledge processing)
1. Data mining 2. Bioinformatics — Data processing
I. Wang, Jason T. L.
006.3′12
ISBN 1852336714
Library of Congress Cataloging-in-Publication Data
A catalogue record for this book is available from the American Library of Congress.
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 repro-
duced, 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 licences
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should be sent to the publishers.
AI&KP ISSN 1610-3947
ISBN 1-85233-671-4 Springer London Berlin Heidelberg
Springer Science+Business Media
springeronline.com
©
Springer-Verlag London Limited 2005
The use of registered names, trademarks, etc. in this publication does not imply, even in the absence
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Typesetting: Electronic text files prepared by authors
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34/3830-543210 Printed on acid-free paper SPIN 10886107
Contents
Contributors
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Part I. Overview
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.
Introduction to Data Mining in Bioinformatics
. . . . . . . . . . .
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2 Organization of the Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.3 Support on the Web . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Survey of Biodata Analysis from a Data Mining
Perspective
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2 Data Cleaning, Data Preprocessing, and Data Integration . . .
2.3 Exploration of Data Mining Tools for Biodata Analysis . . . . . .
2.4 Discovery of Frequent Sequential and Structured Patterns . . .
2.5 Classification Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.6 Cluster Analysis Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.7 Computational Modeling of Biological Networks . . . . . . . . . . . .
2.8 Data Visualization and Visual Data Mining . . . . . . . . . . . . . . . .
2.9 Emerging Frontiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.10 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
ix
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2.
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Part II. Sequence and Structure Alignment
. . . . . . . . . . . . . . . . . . .
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3.
AntiClustAl: Multiple Sequence Alignment by Antipole
Clustering
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 Antipole Tree Data Structure for Clustering . . . . . . . . . . . . . . .
3.4 AntiClustAl: Multiple Sequence Alignment via Antipoles . . . .
3.5 Comparing ClustalW and AntiClustAl . . . . . . . . . . . . . . . . . . . .
3.6 Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.8 Future Developments and Research Problems . . . . . . . . . . . . . .
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