6 papers
HistoMet: A Pan-Cancer Deep Learning Framework for Prognostic Prediction of Metastatic Progression and Site Tropism from Primary Tumor Histopathology
Yixin Chen, Ziyu Su, Lingbin Meng +4
Metastatic Progression remains the leading cause of cancer-related mortality, yet predicting whether a primary tumor will metastasize and where it will disseminate directly from hi…
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…
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…
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…
Large Language Models Meet Graph Neural Networks for Text-Numeric Graph Reasoning
Haoran Song, Jiarui Feng, Guangfu Li +4
In real-world scientific discovery, human beings always make use of the accumulated prior knowledge with imagination pick select one or a few most promising hypotheses from large a…
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)…