Machine Learning Approaches To Bioinformatics

E-Book Overview

This book covers a wide range of subjects in applying machine learning approaches for bioinformatics projects. The book succeeds on two key unique features. First, it introduces the most widely used machine learning approaches in bioinformatics and discusses, with evaluations from real case studies, how they are used in individual bioinformatics projects. Second, it introduces state-of-the-art bioinformatics research methods. The theoretical parts and the practical parts are well integrated for readers to follow the existing procedures in individual research. Unlike most of the bioinformatics books on the market, the content coverage is not limited to just one subject. A broad spectrum of relevant topics in bioinformatics including systematic data mining and computational systems biology researches are brought together in this book, thereby offering an efficient and convenient platform for teaching purposes. An essential reference for both final year undergraduates and graduate students in universities, as well as a comprehensive handbook for new researchers, this book will also serve as a practical guide for software development in relevant bioinformatics projects.

E-Book Content

machine learning approaches to bioinformatics SCIENCE, ENGINEERING, AND BIOLOGY INFORMATICS Series Editor: Jason T. L. Wang (New Jersey Institute of Technology, USA) Published: Vol. 1: Advanced Analysis of Gene Expression Microarray Data (Aidong Zhang) Vol. 2: Life Science Data Mining (Stephen T. C. Wong & Chung-Sheng Li) Vol. 3: Analysis of Biological Data: A Soft Computing Approach (Sanghamitra Bandyopadhyay, Ujjwal Maulik & Jason T. L. Wang) Vol. 4: Machine Learning Approaches to Bioinformatics (Zheng Rong Yang) Forthcoming: Vol. 5: Biodata Mining and Visualization: Novel Approaches (Ilkka Havukkala) XiaoLing - Machine Learning Approaches.pmd 2 4/5/2010, 6:52 PM machine learning approaches to bioinformatics zheng rong yang University of Exeter, UK World Scientific NEW JERSEY • LONDON • SINGAPORE • BEIJING • SHANGHAI • HONG KONG • TA I P E I • CHENNAI Published by World Scientific Publishing Co. Pte. Ltd. 5 Toh Tuck Link, Singapore 596224 USA office: 27 Warren Street, Suite 401-402, Hackensack, NJ 07601 UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library. Science, Engineering, and Biology Informatics — Vol. 4 MACHINE LEARNING APPROACHES TO BIOINFORMATICS Copyright © 2010 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. This book, or parts thereof, may not be reproduced in any form or by any means, electronic or mechanical, including photocopying, recording or any information storage and retrieval system now known or to be invented, without written permission from the Publisher. For photocopying of material in this volume, please pay a copying fee through the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA. In this case permission to photocopy is not required from the publisher. ISBN-13 978-981-4287-30-2 ISBN-10 981-4287-30-X Printed in Singapore. XiaoLing - Machine Learning Approaches.pmd 1 4/5/2010, 6:52 PM Preface Bioinformatics has been one of the most important multidisciplinary subjects in the last century. Initially, the major task of bioinformatics research was to handle large genomic data for knowledge extraction and for making predictions. More recently, the practices of bioinformatics have extended from genomics to pro
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