Computational Methods for the Prediction of Protein-Protein Interactions
Jun-Feng Xia, Shu-Lin Wang and Ying-Ke Lei
Affiliation: Intelligent Computing Lab, Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, 230031, China.
Protein-protein interactions (PPIs) are key components of most cellular processes, so identification of PPIs is at the heart of functional genomics. A number of experimental techniques have been developed to discover the PPI networks of several organisms. However, the accuracy and coverage of these techniques have proven to be limited. Therefore, it is important to develop computational methods to assist in the design and validation of experimental studies and for the prediction of interaction partners. Here, we provide a critical overview of existing computational methods including genomic context method, structure-based method, domain-based method and sequence-based method. While an exhaustive list of methods is not presented, we analyze the relative strengths and weaknesses for each of the methods discussed, as well as a broader perspective on computational techniques for determining PPIs. In addition to algorithms for interaction prediction, description of many useful databases pertaining to PPIs is also provided.
Keywords: Protein-protein interactions, computational techniques, genome context, protein structure, protein domain, protein sequence, protein interaction databases
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