Hierarchical graph learning for protein–protein interaction

• Published in: Nature communications Vol. 14; no. 1; p. 1093
• Main Authors: Gao, Ziqi, Jiang, Chenran, Zhang, Jiawen, Jiang, Xiaosen, Li, Lanqing, Zhao, Peilin, Yang, Huanming, Huang, Yong, Li, Jia
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 25.02.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 119/118; 631/114/1305; 631/114/2784; Active sites; Amino Acid Sequence; Computer applications; Deep Learning; Humanities and Social Sciences; Humans; Machine learning; Model accuracy; Modelling; multidisciplinary; Predictions; Protein interaction; Protein Interaction Mapping - methods; Protein Interaction Maps; Proteins; Proteins - metabolism; Science; Science (multidisciplinary); Sequences; Software; Structure-function relationships

Protein-Protein Interactions (PPIs) are fundamental means of functions and signalings in biological systems. The massive growth in demand and cost associated with experimental PPI studies calls for computational tools for automated prediction and understanding of PPIs. Despite recent progress, in si...