Hur Lab

Integrative multi-omics analysis and network-based approaches to uncover molecular mechanisms in complex diseases.

Biomedical ontology development and knowledge representation for standardized data integration and analysis.

Large language models, natural language processing and deep learning for biomedical data: knowledge extraction from the literature, biological age prediction and disease modeling. We are also building agentic AI workflows in which AI agents carry out bioinformatics and data-science analyses under human review.

Computational analysis of diabetic neuropathy, ALS, and other neurological conditions through transcriptomic profiling.

Literature mining and ontology-driven analysis of host-pathogen molecular interactions and immune response networks.

Network and cheminformatics modeling of drug-induced adverse events, polypharmacy risk, and drug repurposing.

Epidemiological and clinical studies of pregnancy outcomes, sleep, metabolic syndrome, biological aging, and long COVID using national surveys and cohorts.