Figure 1.

Overview of machine learning approaches to predicting protein–protein interaction hot spots. For the binding of interface residues in protein–protein interactions, a large number and variety of features are extracted from diverse data sources. Then feature extraction and feature selection approaches are used for dimensionality reduction. Finally, the machine learning-based prediction models are trained and applied to make predictions of hot spots.