① 연구실명 : 유전자교정 연구실 (Genome Editing Laboratory)
② 지도교수명 : 김희권 교수 (Prof. Kim, Hui Kwon)
③ 연구실 소개
안녕하세요, 성균관대학교 생명공학대학 융합생명공학과 '유전자교정 연구실' 입니다. 유전자교정기술은 유전자치료제 및 세포치료제 개발의 핵심기술이며, 또한 유전학 연구, 분자 이미징, 합성생물학 등 다양한 연구분야들에도 널리 활용되고 있습니다. 우리 연구실에서는 유전자교정기술에 인공지능을 접목시킴으로써 보다 안전하고 효과적인 유전자치료제를 개발하고자 합니다. 더불어 우리 유전체를 구성하는 DNA에 담긴 새로운 지식을 탐구하고자 하며, 이를 위해 DNA정보를 대량으로 읽고, 쓸 수 있는 분자생물공학 기술들을 개발하고 적용하고 있습니다. 연구실 이메일 주소는 huikwonkim@skku.edu입니다. 연구에 대한 재능과 열정이 있는 분들의 많은 연락바랍니다. 감사합니다.
'Genome Editing Laboratory' is one of the newly established laboratories in the Department of Integrative Biotechnology. Genome editing technology has been widely used for the development of gene and cell therapeutics. As such, the technology has been proven to exhibit a wide-range of biological applications such as functional genomics, molecular imaging, and synthetic biology. Currently, our team is working on developing a safer and more efficient method for gene therapeutics by integrating deep learning with genome editing technologies. Our lab is also interested in the development of methods that can precisely read and write DNAs to significantly broadening our knowledge about molecular processes in human cells. We are always seeking talented and passionate students and researchers to join our team. If you are interested in joining us, please feel free to contact me (huikwonkim@skku.edu).
④ 연구분야
유전자교정기술 / 유전자치료제 / 분자생물공학 / 인공지능 및 머신러닝
⑤ 대표연구 실적
■ Kim, H.K*., Yoo, G*., Park, J., Min, S., Lee, S., Yoon, S., Kim, H.H. Predicting the efficiency of prime-editing guide RNAs in human cells. Nature Biotechnology, 2021. Impact factor = 36.553
■ Kim, N*., Kim, H.K*., Lee, S., Seo, J.H., Choi, J.W., Park, J., Min, S., Yoon, S., Cho, S-R., Kim, H.H. Prediction of the sequence-specific cleavage activity of Cas9 variants. Nature Biotechnology, 2020. Impact factor = 36.553
■ Song, M*., Kim, H.K*., Lee, S*., Kim, Y., Seo, S.Y., Park, J., Choi, J.W., Jang, H., Shin, J.H., Min, S., Quan, Z., Kim, J.H., Kang, H.C., Yoon, S., Kim, H.H. Sequence-specific prediction of the efficiencies of adenine and cytosine base editors. Nature Biotechnology, 2020. Impact factor = 36.553
■ Kim, H.K., Lee, S., Kim, Y., Park, J., Min, S., Choi, J.W., Huang, T.P., Yoon, S., Liu, D.R., Kim, H.H. High-throughput analysis of the activities of xCas9, SpCas9-NG and SpCas9 at matched and mismatched target sequences in human cells. Nature Biomedical Engineering, 2020. Impact factor = 18.952
■ Kim, H.K*., Kim, Y*., Lee, S., Min, S., Bae, J.Y., Choi, J.W., Park, J., Jung, D., Yoon, S., Kim, H.H. SpCas9 activity prediction by DeepSpCas9, a deep learning-based model with high generalization performance. Science Advances, 2019. Impact factor = 13.117
■ Kim, H.K*., Min, S*., Song, M., Jung, S., Choi, J.W., Kim, Y., Lee, S., Yoon, S#., Kim, H.H#. Deep learning improves prediction of CRISPR–Cpf1 guide RNA activity. Nature Biotechnology, 2018. Impact factor = 36.553
■ Kim, H.K*., Song, M*., Lee, J., Menon, A.V., Jung, S., Kang, Y.M., Choi, J.W., Woo, E., Koh, H.C., Nam, J.W., Kim, H.H. In vivo high-throughput profiling of CRISPR-Cpf1 activity. Nature Methods, 2017. Impact factor = 30.822
* and # denote co-first authors and co-corresponding authors, respectively.
⑥ 대표전화 : 031-290-7860
⑦ 위치 : 생명공학관 62동 2층 62208호