Yan Wang

HyperDFI: Cross-View Hypergraph-Graph Contrastive Learning for Drug-Food Interaction Prediction

Drug-food interactions (DFIs) are one of the major factors that trigger adverse drug events and have important research and clinical application value. However, experimental identification of DFIs remains costly and limited in scalability, leading to insufficient coverage of known interactions. Existing computational...

MDCL: Multi-source Information Fusion and Collaborative Contrastive Learning for Inferring miRNA-Drug Sensitivity and Resistance Associations.

GATESynergy: Integrating Molecular Global-Local Aggregator and Hierarchical Gene-Gated Encoder for Drug Synergy Prediction.

GATESynergy is a novel deep learning framework for predicting drug synergy that combines a hierarchical gated gene-aware encoder (HiGate) with a molecular global-local aggregator (MoGLA) that uses global query summarization to efficiently fuse drug-drug-cell line representations and capture diverse synergistic interact...

ProtSyntax: a protein large language model for decoding post-translational modification syntax and function

ProtSyntax is introduced, a PTM-aware foundation protein language model combining protein-aware positional encoding, bidirectional state-space propagation, geometry-constrained attention and adaptive multi-objective learning that has the potential to decode the regulatory language of the modified proteome.