백대현 Baek, Daehyun
Artificial Intelligence (Deep Learning) for Biology and Medicine
- Deep neural networks (DNNs) for RNA biology: microRNA targeting, RNA-binding proteins, RNA modifications, and alternative mRNA processing
- DNNs for cancer genomics: detection of cancer mutations and estimation of tumor evolution
Computational Biology and Bioinformatics
- Large-scale sequence analysis
- Bio big data: genome, transcriptome, and proteome
- MicroRNA targeting and biogenesis
- RNA-binding proteins
- Alternative mRNA splicing and alternative promoters
- Integrated multi-omics analysis of disease genome, transcriptome, and proteome
- Development of disease (including cancer and diabetes) genome analysis software
- D. Kim*, Y. M. Sung*, J. Park*, S. Kim, J. Kim, J. Park, H. Ha, J. Y. Bae, S. Kim, and D. Baek, General Rules for Functional MicroRNA Targeting, Nature Genetics, 2016
- D. Garcia*, D. Baek*#, C. Shin, G. Bell, A. Grimson, and D. Bartel#, Weak Seed-Pairing Stability and High Target-Site Abundance Decrease the Proficiency of lsy-6 and Other miRNAs, Nature Structural and Molecular Biology, 2011.
(*co-first authors, #co-corresponding authors)
- D. Baek*, J. Villen*, C. Shin*, F. Camargo, S. Gygi, and D. Bartel, The Impact of MicroRNAs on Protein Output, Nature, 2008.
- D. Baek#, C. Davis, B. Ewing, D. Gordon, and P. Green#, Characterization and Predictive Discovery of Evolutionarily Conserved Mammalian Alternative Promoters, Genome Research, 2007.
- D. Baek# and P. Green#, Sequence Conservation, Relative Isoform Frequencies, and Nonsense-Mediated Decay in Evolutionarily Conserved Alternative Splicing, Proceedings of the National Academy of Sciences U.S.A., 2005.