Protein Interaction Networks: Computational Analysis

Protein Interaction Networks: Computational Analysis

by Aidong Zhang (Author)

Synopsis

The analysis of protein-protein interactions is fundamental to the understanding of cellular organization, processes, and functions. Proteins seldom act as single isolated species; rather, proteins involved in the same cellular processes often interact with each other. Functions of uncharacterized proteins can be predicted through comparison with the interactions of similar known proteins. Recent large-scale investigations of protein-protein interactions using such techniques as two-hybrid systems, mass spectrometry, and protein microarrays have enriched the available protein interaction data and facilitated the construction of integrated protein-protein interaction networks. The resulting large volume of protein-protein interaction data has posed a challenge to experimental investigation. This book provides a comprehensive understanding of the computational methods available for the analysis of protein-protein interaction networks. It offers an in-depth survey of a range of approaches, including statistical, topological, data-mining, and ontology-based methods. The author discusses the fundamental principles underlying each of these approaches and their respective benefits and drawbacks, and she offers suggestions for future research.

$97.22

Quantity

20+ in stock

More Information

Format: Hardcover
Pages: 292
Edition: 1
Publisher: Cambridge University Press
Published: 06 Apr 2009

ISBN 10: 0521888956
ISBN 13: 9780521888950

Media Reviews
Up-to-date on the research and thoroughly comprehensive in coverage, Aidong Zhang's Protein Interaction Networks: Computational Analysis is an invaluable contribution to our understanding and knowledge of current analytic methods for protein interaction networks. Written with technical depth and sophistication, and replete with examples, this book will be both an indispensable manual for practitioners and a crucial textbook for teaching. Jiawei Han, Professor of Computer Science, University of Illinois at Urbana-Champaign
This book provides a comprehensive coverage of current research issues and solutions in protein interaction networks. Within this new and exciting area of research, certain topics are explored in depth, including newest results reported by the author and other leading experts. I highly recommend this book for researchers and students who are interested in bioinformatics. Yi Pan, Chair and Professor of Computer Science, Georgia State University
This book provides the most comprehensive and systematic review to an important biomedical research topic (protein interaction network). It gives its readers an opportunity to easily learn about this challenging topic and to begin investigating how they may contribute to it. Its great value makes it suitable for a broad range of readers, from students to experienced researchers. Dong Xu, Professor and Chair of the Computer Science Department, University of Missouri, Columbia
This book is a comprehensive and an excellent introduction to network biology in general and proteins networks in particular. It provides detailed description of the major computational concepts and their applications in systems biology. It is a must have book for anyone interested in this exciting topic. Mohammed J. Zaki, Professor of Computer Science, Rensselaer Polytechnic Institute
Author Bio
Dr Aidong Zhang is a professor in the Department of Computer Science and Engineering at the State University of New York at Buffalo and the director of the Buffalo Center for Biomedical Computing (BCBC). She is an author of more than 190 research publications and has served on the editorial boards of the International Journal of Bioinformatics Research and Applications (IJBRA), ACM Multimedia Systems, the International Journal of Multimedia Tools and Applications, the International Journal of Distributed and Parallel Databases, and ACM SIGMOD DiSC (Digital Symposium Collection). Dr Zhang is a recipient of the National Science Foundation CAREER Award and SUNY (State University of New York) Chancellor's Research Recognition Award.