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• W1979263457 abstract "Cliques (maximal complete subnets) in protein-protein interaction (PPI) network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO) annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP) and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning." @default.
• W1979263457 created "2016-06-24" @default.
• W1979263457 creator A5023071921 @default.
• W1979263457 creator A5089058945 @default.
• W1979263457 date "2014-01-01" @default.
• W1979263457 modified "2023-10-12" @default.
• W1979263457 title "Protein-Protein Interactions Prediction Based on Iterative Clique Extension with Gene Ontology Filtering" @default.
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• W1979263457 doi "https://doi.org/10.1155/2014/523634" @default.
• W1979263457 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3919085" @default.
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