Predicting Tumor Cell Response to Synergistic Drug Combinations Using a Novel Simplified Deep Learning Model. - Heming Zhang 002; Jiarui Feng; Amanda Zeng; Philip R. O. Payne; Fuhai Li 001 (AMIA, 2020)

Investigating the relevance of major signaling pathways in cancer survival using a biologically meaningful deep learning model. - Jiarui Feng; Heming Zhang 002; Fuhai Li 001 (BMC Bioinform., 2021)

Interpretable Drug Synergy Prediction with Graph Neural Networks for Human-AI Collaboration in Healthcare. - Zehao Dong; Heming Zhang 002; Yixin Chen 001; Fuhai Li 001 (CoRR, 2021)

Predicting Anticancer Drug Response With Deep Learning Constrained by Signaling Pathways. - Heming Zhang 002; Yixin Chen 001; Fuhai Li 001 (Frontiers Bioinform., 2021)

GraphSeqLM: A Unified Graph Language Framework for Omic Graph Learning. - Heming Zhang 002; Di Huang; Yixin Chen 001; Fuhai Li 001 (WWW (Companion Volume), 2025)

KoGNER: A Novel Framework for Knowledge Graph Distillation on Biomedical Named Entity Recognition. - Heming Zhang 002; Wenyu Li; Di Huang; Yinjie Tang; Yixin Chen 001; Philip R. O. Payne; Fuhai Li 001 (CoRR, 2025)

OmniCellTOSG: The First Cell Text-Omic Signaling Graphs Dataset for Joint LLM and GNN Modeling. - Heming Zhang 002; Tim Xu; Dekang Cao; Shunning Liang; Lars Schimmelpfennig; Levi Kaster; Di Huang; Carlos Cruchaga; Guangfu Li; Michael A. Province; Yixin Chen 001; Philip R. O. Payne; et al. (CoRR, 2025)