Pattern Recognition in Bioinformatics Second IAPR International
The advancements of computational and informational techniques have enabled in silico testing of many lab-based experiments in life sciences before performing them in in vitro or in vivo. Though computational techniques are not capable of mimicking all we
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Edited by S. Istrail, P. Pevzner, and M. Waterman Editorial Board: A. Apostolico S. Brunak M. Gelfand T. Lengauer S. Miyano G. Myers M.-F. Sagot D. Sankoff R. Shamir T. Speed M. Vingron W. Wong
Subseries of Lecture Notes in Computer Science
Jagath C. Rajapakse Bertil Schmidt Gwenn Volkert (Eds.)
Pattern Recognition in Bioinformatics Second IAPR International Workshop, PRIB 2007 Singapore, October 1-2, 2007 Proceedings
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Series Editors Sorin Istrail, Brown University, Providence, RI, USA Pavel Pevzner, University of California, San Diego, CA, USA Michael Waterman, University of Southern California, Los Angeles, CA, USA Volume Editors Jagath C. Rajapakse Nanyang Technolocial University, Singapore E-mail: [email protected] Bertil Schmidt University of New South Wales Asia, Singapore E-mail: [email protected] Gwenn Volkert Kent State University, USA E-mail: [email protected]
Library of Congress Control Number: Applied for
CR Subject Classification (1998): H.2.8, I.5, I.4, J.3, I.2, H.3, F.1-2 LNCS Sublibrary: SL 8 – Bioinformatics ISSN ISBN-10 ISBN-13
0302-9743 3-540-75285-4 Springer Berlin Heidelberg New York 978-3-540-75285-1 Springer Berlin Heidelberg New York
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Preface
The advancements of computational and informational techniques have enabled in silico testing of many lab-based experiments in life sciences before performing them in in vitro or in vivo. Though computational techniques are not capable of mimicking all wet-lab experiments, bioinformatics will inevitably play a major role in future medical practice. For example, in the pursuit of new drugs it can reduce the costs and complexity involved in expensive wet-lab experiments. It is expected that by 2010, sequencing of individual genomes will be affordable generating an unprecedented increase of life sciences data, in the form of sequences, expressions, networks, images, literature. Pattern recognition techniques lie at the heart of discovery of new insights into biological knowledge, as the presence of particular patterns or structure is often an indication of its function. The aim of the workshop series Pattern Recognition in Bioinformatics (PRIB) is to bring pattern
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