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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.
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