Zhen-Hao Guo

CAMEX integrates, aligns, and annotates multi-species scRNA-seq data using a GNN, outperforming existing methods and enabling species-specific cell type detection.

STAX is a multi-task learning platform for spatial omics that addresses multiple analytical challenges, offering superior performance and biological insights.

MetaboliteChat is a multimodal LLM that integrates molecular graphs and images with natural language to provide interactive metabolite analysis and functional insights.

This paper introduces MeSHHeading2vec, a method that represents MeSH headings as vectors using graph embedding algorithms, showing improved performance in node classification and relationship prediction tasks.

The paper introduces iMDA-BN, a computational model for predicting miRNA-disease associations using biological networks and graph embedding, achieving high accuracy on benchmark datasets.

The paper introduces Biomarker2vec, a method that predicts multi-type relationships between biomarkers using a heterogeneous network and vector representation, achieving high performance on 18 relationships.

The paper constructs a large-scale molecular associations network integrating multiple biomolecules and predicts interactions with high accuracy.