Protein Interaction Networks: Computational Analysis

Aidong Zhang

doi:10.1017/CBO9780511626593

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.

"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

Protein Interaction Networks

Computational Analysis

This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

Book description

Reviews

Refine List

Actions for selected content:

Contents

Frontmatter
pp i-vi

Contents
pp vii-xii

Preface
pp xiii-xiv

1 - Introduction
pp 1-10

2 - Experimental Approaches to Generation of PPI Data
pp 11-20

3 - Computational Methods for the Prediction of PPIs
pp 21-32

4 - Basic Properties and Measurements of Protein Interaction Networks
pp 33-49

5 - Modularity Analysis of Protein Interaction Networks
pp 50-62

6 - Topological Analysis of Protein Interaction Networks
pp 63-108

7 - Distance-Based Modularity Analysis
pp 109-129

8 - Graph-Theoretic Approaches to Modularity Analysis
pp 130-151

9 - Flow-Based Analysis of Protein Interaction Networks
pp 152-198

10 - Statistics and Machine Learning Based Analysis of Protein Interaction Networks
pp 199-215

11 - Integration of GO into the Analysis of Protein Interaction Networks
pp 216-242

12 - Data Fusion in the Analysis of Protein Interaction Networks
pp 243-250

13 - Conclusion
pp 251-254

Bibliography
pp 255-272

Index
pp 273-278

Metrics

Altmetric attention score

Full text views

Book summary page views