7 papers
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…
RC-GRPO: Reward-Conditioned Group Relative Policy Optimization for Multi-Turn Tool Calling Agents
Haitian Zhong, Jixiu Zhai, Lei Song +3
Multi-turn tool calling is challenging for Large Language Models (LLMs) because rewards are sparse and exploration is expensive. A common recipe, SFT followed by GRPO, can stall wh…
A general language model for peptide function identification
Jixiu Zhai, Zikun Wang, Chupei Tang +7
Accurate identification of bioactive peptides (BPs) and protein post-translational modifications (PTMs) is essential for understanding protein function and advancing therapeutic di…