Qian Zhu

RD-OMICS integrates and structures rare disease omics data from GEO into a knowledge graph to support research and drug repurposing.

The paper identifies six potential biomarkers for CLN3 disease using proteomics data and machine learning, with some showing differential expression linked to disease progression.

The paper explores NCATS biomedical data to identify drug repurposing candidates through chemical clustering and evidence mining.

The paper clusters rare diseases using a knowledge graph with node embeddings, identifying 37 clusters with shared genes and semantic similarities.