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Domain-Based Prediction and Analysis of Protein-Protein Interactions
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Author(s): Tatsuya Akutsu (Kyoto University, Japan)and Morihiro Hayashida (Kyoto University, Japan)
Copyright: 2009
Pages: 16
Source title:
Biological Data Mining in Protein Interaction Networks
Source Author(s)/Editor(s): Xiao-Li Li (Institute for Infocomm Research, A* STAR, Singapore)and See-Kiong Ng (Institute for Infocomm Research, A* STAR, Singapore)
DOI: 10.4018/978-1-60566-398-2.ch003
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Abstract
Many methods have been proposed for inference of protein-protein interactions from protein sequence data. This chapter focuses on methods based on domain-domain interactions, where a domain is defined as a region within a protein that either performs a specific function or constitutes a stable structural unit. In these methods, the probabilities of domain-domain interactions are inferred from known protein-protein interaction data and protein domain data, and then prediction of interactions is performed based on these probabilities and contents of domains of given proteins. This chapter overviews several fundamental methods, which include association method, expectation maximization-based method, support vector machine-based method, and linear programmingbased method. This chapter also reviews a simple evolutionary model of protein domains, which yields a scalefree distribution of protein domains. By combining with a domain-based protein interaction model, a scale-free distribution of protein-protein interaction networks is also derived.
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