Jae K. Lee, PhD
Statistics and bioinformatics; genetic data mining
Dr. Lee has worked on statistical research in molecular genetics and bioinformatics, including genetic population inference, DNA structure analysis, linkage association study, and high-throughput gene chip data analysis on cancer and other biomedical studies. In particular, he has developed computational statistical approaches to anticancer gene-drug discovery and pioneered the statistical development of small-sample microarray data analysis techniques such as LPE (local pooled error) and HEM (heterogeneous error model), which are frequently required in many practical, genomic biomedical investigations. Dr. Lee currently leads the large-screening microarray study of cancer immunology comparing the melanoma patient groups of long-term survivors vs. rapid-progressors on various T-cell subpopulations, and serves as Director of the UVA GeneChip/Microarray Bioinformatics Core (GMB), which provides UVA and public researchers statistical, computational, and bioinformatics support for their microarray studies, together with the open source development of the GEOSS database/analysis server.