Computational Biology & Artificial Intelligence
University of North Dakota
Developing computational methods to understand complex biological systems and human diseases
Our interdisciplinary research spans computational biology, AI, and biomedical informatics
Integrative multi-omics analysis and network-based approaches to uncover molecular mechanisms in complex diseases.
Learn moreBiomedical ontology development and knowledge representation for standardized data integration and analysis.
Learn moreDeep learning and machine learning models for biomarker discovery, drug response prediction, and single-cell analysis.
Learn moreComputational analysis of diabetic neuropathy, ALS, and other neurological conditions through transcriptomic profiling.
Learn moreLiterature mining and ontology-driven analysis of host-pathogen molecular interactions and immune response networks.
Learn moreLatest peer-reviewed research from the Hur Lab
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Open-source software developed by our lab for the research community
Functional enrichment and visualization R package for comprehensive pathway analysis with support for multiple annotation databases.
Gene-aware embedding network for single-cell RNA-seq clustering using deep learning for improved cell-type identification.