<ul data-eligibleForWebStory="false"><li>Researchers have proposed a hierarchical contrastive framework, HIPPO, for protein-protein interaction (PPI) prediction involving protein sequences and hierarchical attributes.</li><li>HIPPO incorporates hierarchical contrastive loss functions to capture structured relationships among functional classes of proteins and adaptively incorporates domain and family knowledge.</li><li>Experiments show that HIPPO outperforms existing methods in PPI prediction, demonstrating robustness in low-data scenarios and strong transferability to other species without retraining.</li><li>The proposed framework's hierarchical feature fusion is crucial for capturing conserved interaction determinants, enabling reliable PPI prediction even in less characterized organisms.</li></ul>

Hierarchical Multi-Label Contrastive Learning for Protein-Protein Interaction Prediction Across Organisms

Discover more