6 papers
Graph-Augmented Topological Internalization with Dual-Stream Classifiers for Medical Report Generation
Moyu Tang, Chupei Tang, Junxiao Kong +2
Automated medical report generation, MRG, holds substantial value for alleviating radiologist workload and enhancing diagnostic efficiency. However, mainstream approaches typically…
PathMoG: A Pathway-Centric Modular Graph Neural Network for Multi-Omics Survival Prediction
Di Wang, Chupei Tang, Junxiao Kong +3
Cancer survival prediction from multi-omics data remains challenging because prognostic signals are high-dimensional, heterogeneous, and distributed across interacting genes and pa…
HBGSA: Hydrogen Bond Graph with Self-Attention for Drug-Target Binding Affinity Prediction
Junxiao Kong, Chupei Tang, Di Wang +4
Accurate prediction of drug-target binding affinity accelerates drug discovery by prioritizing compounds for experimental validation. Current methods face three limitations: sequen…
An Integrated Deep-Learning Framework for Peptide-Protein Interaction Prediction and Target-Conditioned Peptide Generation with ConGA-PepPI and TC-PepGen
Chupei Tang, Junxiao Kong, Moyu Tang +5
Motivation: Peptide-protein interactions (PepPIs) are central to cellular regulation and peptide therapeutics, but experimental characterization remains too slow for large-scale sc…
MEDNA-DFM: A Dual-View FiLM-MoE Model for Explainable DNA Methylation Prediction
Yi He, Yina Cao, Jixiu Zhai +3
Accurate computational identification of DNA methylation is essential for understanding epigenetic regulation. Although deep learning excels in this binary classification task, its…
SCMPPI: Supervised Contrastive Multimodal Framework for Predicting Protein-Protein Interactions
Shengrui XU, Tianchi Lu, Zikun Wang +1
Protein-protein interaction (PPI) prediction plays a pivotal role in deciphering cellular functions and disease mechanisms. To address the limitations of traditional experimental m…