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Protein-protein interactions (PPIs) are involved with most cellular activities at the proteomic level, making the study of PPIs necessary to comprehending any biological process. Machine learning approaches have been explored, leading to more accurate and generalized PPIs predictions. In this paper, we propose a predictive framework called StackPPI. First, we use pseudo amino acid composition, Moreau-Broto, Moran and Geary autocorrelation descriptor, amino acid composition position-specific scoring matrix, Bi-gram position-specific sco
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