2 citations · 4 across the 5 of their papers we have counts for
5 papers
GALAX: Graph-Augmented Language Model for Explainable Reinforcement-Guided Subgraph Reasoning in Precision Medicine
Heming Zhang, Di Huang, Wenyu Li +4
In precision medicine, quantitative multi-omic features, topological context, and textual biological knowledge play vital roles in identifying disease-critical signaling pathways a…
OmniCellTOSG: The First Cell Text-Omic Signaling Graphs Dataset for Graph Language Foundation Modeling
Heming Zhang, Tim Xu, Dekang Cao +22
With the rapid growth of large-scale single-cell omic datasets, omic foundation models (FMs) have emerged as powerful tools for advancing research in life sciences and precision me…
KoGNER: A Novel Framework for Knowledge Graph Distillation on Biomedical Named Entity Recognition
Heming Zhang, Wenyu Li, Di Huang +4
Named Entity Recognition (NER) is a fundamental task in Natural Language Processing (NLP) that plays a crucial role in information extraction, question answering, and knowledge-bas…
GraphSeqLM: A Unified Graph Language Framework for Omic Graph Learning
Heming Zhang, Di Huang, Yixin Chen +1
The integration of multi-omic data is pivotal for understanding complex diseases, but its high dimensionality and noise present significant challenges. Graph Neural Networks (GNNs)…
Interpretable Drug Synergy Prediction with Graph Neural Networks for Human-AI Collaboration in Healthcare
Zehao Dong, Heming Zhang, Yixin Chen +1
We investigate molecular mechanisms of resistant or sensitive response of cancer drug combination therapies in an inductive and interpretable manner. Though deep learning algorithm…