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Protein Interaction Networks: Protein Domain Interaction and Protein Function Prediction

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Handbook of Statistical Bioinformatics

Part of the book series: Springer Handbooks of Computational Statistics ((SHCS))

Abstract

Most of a cell’s functional processes involve interactions among proteins, and a key challenge in proteomics is to better understand these complex interaction graphs at a systems level. Because of their importance in development and disease, protein-protein interactions (PPIs) have been the subject of intense research in recent years. In addition, a greater understanding of PPIs can be achieved through the detailed investigation of the protein domain interactions which mediate PPIs. In this chapter, we describe recent efforts to predict interactions between proteins and between protein domains. We also describe methods that attempt to use protein interaction data to infer protein function. Protein-protein interactions directly contribute to protein functions, and implications about functions can often be made via PPI studies. These inferences are based on the premise that the function of a protein may be discovered by studying its interaction with one or more proteins of known functions. The second part of this chapter reviews recent computational approaches to predict protein functions from PPI networks.

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Correspondence to William Stafford Noble .

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Qi, Y., Noble, W.S. (2011). Protein Interaction Networks: Protein Domain Interaction and Protein Function Prediction. In: Lu, HS., Schölkopf, B., Zhao, H. (eds) Handbook of Statistical Bioinformatics. Springer Handbooks of Computational Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16345-6_21

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