… site prediction, we assume the interaction sites to represent the positive samples and non-interaction
sites … To evaluate the performance of our model and other methods in PPI sites, six …

… Summary: A number of complementary methods have been developed for predicting
protein-protein interaction sites. We sought to increase prediction robustness and accuracy by …

… Interaction sites on protein surfaces mediate virtually all … Novel algorithmic approaches for
the prediction of these sites … for modern protein-protein interaction site (PPIS) prediction, and …

… Protein interaction sites have often been used almost interchangeably with functional sites.
As seen earlier, in prediction of interaction sites, structural and physical attributes have been …

… In order to predict protein–protein interaction sites, we address this problem as a sequence
labeling task. Protein surface residues were extracted and the surface residue segments …

… set was used for the prediction of the interaction site ratio; 1/3 … for interaction site prediction
using the actual interaction site … used for the test set, ie the interaction site ratio for 1/10 of the …

… Prediction of Highly probable protein Interaction sites (DELPHI), a new sequence-based deep
learning suite for PPI-binding sites prediction. … protein-binding residues (PBRs) and sites …

… —a task known as PPI site prediction—are outlined. … protein–protein interaction site
prediction, and an introduction to developing geometric deep learning projects operating on protein …

… on the 226 protein heterodimers of the selected data set, performs with a 73% per residue
accuracy. To further test our method we also predict the protein–protein interaction sites of the …

… for structure-based prediction of Protein–Protein-Interacting Site (GraphPPIS). Specifically,
we considered a protein as an undirected graph and PPI site prediction as a graph node …