Protein Networks and Pathway Analysis
From the beginning of the OMICs biology era, science has been pursuing the reduction of the complex "genome-wide" assays in order to understand the essential biology that lies beneath it. In Protein Networks and Pathway Analysis, expert practitioner
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Protein Networks and Pathway Analysis Edited by
Yuri Nikolsky Julie Bryant
METHODS
IN
M O L E C U L A R B I O L O G Y TM
Series Editor John M. Walker School of Life Sciences University of Hertfordshire Hatfield, Hertfordshire, AL10 9AB, UK
For other titles published in this series, go to www.springer.com/series/7651
Protein Networks and Pathway Analysis Edited by
Yuri Nikolsky and Julie Bryant GeneGo, Inc., Encinitas CA, USA
Editors Yuri Nikolsky GeneGo Inc. Encinitas, CA 92024 USA [email protected]
Julie Bryant GeneGO Inc. Encinitas, CA 92024 USA [email protected]
Series Editor John Walker Halfield, Hertfordshire AL10 9NP UK
ISBN 978-1-60761-174-5 e-ISBN 978-1-60761-175-2 DOI 10.1007/978-1-60761-175-2 Springer Dordrecht Heidelberg London New York Library of Congress Control Number: 2009929229 # Humana Press, a part of Springer ScienceþBusiness Media, LLC 2009 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Humana Press, c/o Springer ScienceþBusiness 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 ScienceþBusiness Media (www.springer.com)
Preface Recent Google queries for ‘‘systems biology’’ and ‘‘pathway analysis’’ fetched over 14 and 2 million entries, respectively. These numbers speak volumes about the ubiquity and popularity of systems data analysis in modern bioscience. These days, any microarray expression or SNP-based article would feature a chapter on pathways, ontology enrichment, and/or biological networks. Although a very young field, the applications of systems biology now spread widely from basic research and pre-clinical drug discovery to translational research and personalized health care. Systems biology ‘‘focuses on the systematic study of complex interactions in biological systems, thus using a new perspective (integration instead of reduction) to study them’’ (Wikipedia). From a practical view point, it means integration of accumulated biological knowledge in a computer-readable format and the creation of tools for applying this structured information to the analysis of biological and chemical experimental data. Starting in the 1970s, biochemistry was the first field from which information was put into databases such as BRENDA, EMP/MPW, and, later, KEGG. Over the years, regulation and signaling components were added to biochemistry in the form of protein interaction databases such as HPRD and BIND, and comprehensive ontologies of ce
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