He has been developing machine-learning-based methods to identify non-coding transcripts (Choi and Nam, 2018, BMC Bioinfo.; Choi et al., 2018, Briefings in Bioinfo.) and to predict the 3'-end of transcript (Kim et al., Methods, 2015), and he has been also focusing on reconstructing coding and non-coding transcriptome maps in human (You et al., Genome Res. 2017) and vertebrates (Hong et al., IJMS, 2018). To further understand the interaction between coding and non-coding elements and the regulatory roles in the relationship, he has been developing an efficient CRISPR/Cas system (Kim et al., 2017, Nature Methods), which was applied to the human XIST study, leading to finding of functional elements of Human XIST (Lee et al., Nucleic Acids Res. 2019), identifying a novel lncRNA gene that regulates Wnt signaling pathways in development of squamous cell-tpye carcinoma (You et al., 2019 PNAS), uncovering a novel UPF1-dependent miRNA-mediated mRNA decay pathway (Park et al., 2019 Nature Comm.), identifying novel oncogenic isomir of miR-21 in HCCs (Park et al., 2022, EMM), and constructing interactome maps of human and fly α-arrestins(Lee et al., eLife, 2024). Recently, he has been expanding his interests to genome assembly (Sohn et al., 2018, GigaScience; Sohn et al., 2018, Briefings in Bioinfo.), its related algorithms to efficiently detect genomic variations (Sohn et al., 2022, Nature Biomedical Engineering; Lee et al., Briefings in Bioinfo., 2023) and single-cell transcriptome studies (Cho et al., 2020, Nature Comm; Yoon et al., npj Precision Onco. 2021; Park et al., Briefings in Bioinfo,2021; Yoon et al., Briefings in Bioinfo. 2023; Yoon et al., PLos Genetics 2023). In addition, his group has been developing AI-aided RNA design algorithms to design augmented/aritificial mRNA vaccines, shRNAs, and RNA drugs