I received my bachelor’s degree in Computer Science and Biology from KAIST in Korea. Then, I completed my PhD in Biomedical Engineering at Johns Hopkins University, where I developed new computational methods for predicting DNA regulatory elements under supervision of Dr. Mike Beer. During PhD study, I became interested in how genetic variants in regulatory elements contribute to human complex diseases. I joined Dr. Chakravarti’s lab as a postdoctoral fellow to pursue my interest in human genetics by studying effects of regulatory DNA variants on cardiovascular diseases and traits, such as high blood pressure and electrocardiogram traits.
Lee D. LS-GKM: A new gkm-SVM for large-scale datasets. Bioinformatics btw142 (2016).
Lee D, Gorkin DU, Baker M, Strober BJ, Asoni AL, McCallion AS, Beer MA. A method to predict the impact of regulatory variants from DNA sequence. Nat Genet 47, 955–961 (2015).
Ghandi M*, Lee D*, Mohammad-Noori M, Beer MA. Enhanced regulatory sequence prediction using gapped k-mer features. PLoS Comput Biol 10: e1003711 (2014). *co-first authors
Fletez-Brant C*, Lee D*†, McCallion AS, Beer MA†. kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic datasets. Nucleic Acids Res 41: W544–W556 (2013). *co-first authors, †co-corresponding authors
Lee D, Karchin R, Beer MA. Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res 21:2167-2180 (2011).