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• W2316576535 abstract "Protein-protein interaction has proven to be a valuable piece of biological knowledge and a starting point for understanding the internal workings of the cell. In this paper, we propose a novel method for protein-protein interaction prediction using only the primary structural information of the protein sequence. The method is developed based on inter-domain linker region knowledge and a combination of pairwise similarity and support vector machine techniques. Two protein sequences may interact by the means of the similarities between the domain-linker regions they contain. The method is tested on different datasets from yeast saccharomyces cerevisiae protein interaction and showed higher specificity, sensitivity and accuracy than the maximum likelihood estimation, protein-protein interaction prediction engine and decision forest methods." @default.
• W2316576535 created "2016-06-24" @default.
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• W2316576535 creator A5040640075 @default.
• W2316576535 date "2009-01-01" @default.
• W2316576535 modified "2023-09-26" @default.
• W2316576535 title "Domain Linker Region Knowledge Contributes to Protein-protein Interaction Prediction" @default.
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