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In Methods in molecular biology (Clifton, N.J.)

Protein interactions play a critical role in all biological processes, but experimental identification of protein interactions is a time- and resource-intensive process. The advances in next-generation sequencing and multi-omics technologies have greatly benefited large-scale predictions of protein interactions using machine learning methods. A wide range of tools have been developed to predict protein-protein, protein-nucleic acid, and protein-drug interactions. Here, we discuss the applications, methods, and challenges faced when employing the various prediction methods. We also briefly describe ways to overcome the challenges and prospective future developments in the field of protein interaction biology.

Vora Dhvani Sandip, Kalakoti Yogesh, Sundar Durai


Deep learning, Interaction, Machine learning, Neural networks, PPI, Protein networks