| In vivo high-throughput profiling of CRISPR–Cpf1 activity HK Kim, M Song, J Lee, AV Menon, S Jung, YM Kang, JW Choi, E Woo, ... Nature methods 14 (2), 153-159, 2017 | 204 | 2017 |
| Deep learning improves prediction of CRISPR–Cpf1 guide RNA activity HK Kim, S Min, M Song, S Jung, JW Choi, Y Kim, S Lee, S Yoon, HH Kim Nature biotechnology 36 (3), 239, 2018 | 123 | 2018 |
| The effects of combined dietary probiotics Lactococcus lactis BFE920 and Lactobacillus plantarum FGL0001 on innate immunity and disease resistance in olive flounder … BR Beck, D Kim, J Jeon, SM Lee, HK Kim, OJ Kim, JI Lee, BS Suh, HK Do, ... Fish & shellfish immunology 42 (1), 177-183, 2015 | 105 | 2015 |
| High-throughput analysis of the activities of xCas9, SpCas9-NG and SpCas9 at matched and mismatched target sequences in human cells HK Kim, S Lee, Y Kim, J Park, S Min, JW Choi, TP Huang, S Yoon, DR Liu, ... Nature Biomedical Engineering 4 (1), 111-124, 2020 | 25 | 2020 |
| SpCas9 activity prediction by DeepSpCas9, a deep learning–based model with high generalization performance HK Kim, Y Kim, S Lee, S Min, JY Bae, JW Choi, J Park, D Jung, S Yoon, ... Science advances 5 (11), eaax9249, 2019 | 22 | 2019 |
| Prediction of the sequence-specific cleavage activity of Cas9 variants N Kim, HK Kim, S Lee, JH Seo, JW Choi, J Park, S Min, S Yoon, SR Cho, ... Nature Biotechnology 38 (11), 1328-1336, 2020 | 18 | 2020 |
| Predicting the efficiency of prime editing guide RNAs in human cells HK Kim, G Yu, J Park, S Min, S Lee, S Yoon, HH Kim Nature Biotechnology 39 (2), 198-206, 2021 | 17 | 2021 |
| Sequence-specific prediction of the efficiencies of adenine and cytosine base editors M Song, HK Kim, S Lee, Y Kim, SY Seo, J Park, JW Choi, H Jang, JH Shin, ... Nature Biotechnology 38 (9), 1037-1043, 2020 | 10 | 2020 |
| Recording of elapsed time and temporal information about biological events using Cas9 J Park, JM Lim, I Jung, SJ Heo, J Park, Y Chang, HK Kim, D Jung, JH Yu, ... Cell 184 (4), 1047-1063. e23, 2021 | | 2021 |
