Heming Zhang

This study examines how intelligence and cognitive flexibility influence working memory through brain connectomic gradients and task performance in healthy adults.

This study introduces mosGraphFlow, a graph AI model for analyzing multi-omic data to identify AD-associated biomarkers and signaling pathways, achieving high classification accuracy.

This study introduces a novel interpretable k-hop graph attention network to integrate multi-omics data and infer essential targets and signaling networks, showing improved performance over existing models.

The paper introduces DeepSignalingFlow, a deep learning model that predicts drug combination synergy and interprets the mechanisms of synergy using graph neural networks.

This study introduces DeepSignalingSynergy, a simplified deep learning model that predicts tumor cell response to drug combinations using cancer signaling pathways, showing feasibility with NCI ALMANAC data.