Data Mining for Biomarker Discovery
Data Mining for Biomarker Discovery is designed to motivate collaboration and discussion among various disciplines and will be of interest to students and researchers in engineering, computer science, applied mathematics, medicine, and anyone interested i
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Aims and Scope Optimization has been expanding in all directions at an astonishing rate during the last few decades. New algorithmic and theoretical techniques have been developed, the diffusion into other disciplines has proceeded at a rapid pace, and our knowledge of all aspects of the field has grown even more profound. At the same time, one of the most striking trends in optimization is the constantly increasing emphasis on the interdisciplinary nature of the field. Optimization has been a basic tool in all areas of applied mathematics, engineering, medicine, economics, and other sciences. The series Springer Optimization and Its Applications publishes undergraduate and graduate textbooks, monographs and state-of-the-art expository work that focus on algorithms for solving optimization problems and also study applications involving such problems. Some of the topics covered include nonlinear optimization (convex and nonconvex), network flow problems, stochastic optimization, optimal control, discrete optimization, multi-objective programming, description of software packages, approximation techniques and heuristic approaches.
For further volumes: http://www.springer.com/series/7393
Panos M. Pardalos • Petros Xanthopoulos Michalis Zervakis Editors
Data Mining for Biomarker Discovery
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Editors Panos M. Pardalos Department of Industrial and Systems Engineering University of Florida 401 Weil Hall Gainesville, FL 32611 USA [email protected]
Petros Xanthopoulos Industrial Engineering and Management Systems Department University of Central Florida 4000 Central Florida Blvd. Orlando, FL, 32816 USA [email protected]
Michalis Zervakis Department of Electronic and Computer Engineering Technical University of Crete Chania 73100 Greece [email protected]
ISSN 1931-6828 ISBN 978-1-4614-2106-1 e-ISBN 978-1-4614-2107-8 DOI 10.1007/978-1-4614-2107-8 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2012930131 © Springer Science+Business Media, LLC 2012 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)
To our families
Preface
Life sciences that include, but are not limited to medicine, biology, and neuroscience, are popular for creating large amounts of data. Some of the most prominent examples of such data accumulation
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