Taejun is interested in leveraging long-read whole-genome sequencing data and bioinformatics to improve the accuracy of variant detection. He is engaged in a research project that involves the analysis of long-read whole-genome sequencing data from autism families in Korea. Currently, he is focusing on establishing a pipeline for identifying de novo variants using long-read data and improving its accuracy. Through this, we will be able to determine a more accurate number of de novo variants present in an individual and uncover variants that have a significant impact on autism but were previously undetectable due to technical limitations.

Education & Training

• 2020-present B.Sc., Biosystem and Biomedical Sciences, Korea University