Life System Modeling and Simulation International Conference, LSMS 2
The International Conference on Life System Modeling and Simulation (LSMS) was formed to bring together international researchers and practitioners in the field of life system modeling and simulation as well as life system-inspired theory and methodology.
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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
Kang Li Xin Li George William Irwin Guosen He (Eds.)
Life System Modeling and Simulation International Conference, LSMS 2007 Shanghai, China, September 14-17, 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 Kang Li George William Irwin Queen’s University Belfast School of Electronics, Electrical Engineering and Computer Science Ashby Building, Stranmillis Road, BT9 5AH Belfast, UK E-mail: {K.Li, g.irwin}@ee.qub.ac.uk Xin Li Guosen He Shanghai University, School of Mechatronics and Automation, China E-mail: {su_xinli, guosenhe}@yahoo.com.cn
Library of Congress Control Number: 2007933845
CR Subject Classification (1998): F.2.2, F.2, E.1, G.1, I.2, J.3 LNCS Sublibrary: SL 8 – Bioinformatics ISSN ISBN-10 ISBN-13
1865-0929 3-540-74770-2 Springer Berlin Heidelberg New York 978-3-540-74770-3 Springer Berlin Heidelberg New York
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Preface
The International Conference on Life System Modeling and Simulation (LSMS) was formed to bring together international researchers and practitioners in the field of life system modeling and simulation as well as life system-inspired theory and methodology. The concept of a life system is quite broad. It covers both micro and macro components ranging from cells, tissues and organs across to organisms and ecologic niches. These interact and evolve to produce an overall complex system whose behavior is difficult to comprehend and predict. The arrival of the 21st century has been marked by a resurgence of research interest both in arriving at a systems-level understanding of biology and in applying such knowledge in complex real-world applications. Consequently, computational methods and intelligence in systems, biology, as well as bio-inspired computational intelligence, have emerged as key drivers fo
