| Interpretable RNA foundation model from unannotated data for highly accurate RNA structure and function predictions J Chen, Z Hu, S Sun, Q Tan, Y Wang, Q Yu, L Zong, L Hong, J Xiao, ... arXiv preprint arXiv:2204.00300, 2022 | 60 | 2022 |
| E2Efold-3D: end-to-end deep learning method for accurate de novo RNA 3D structure prediction T Shen, Z Hu, Z Peng, J Chen, P Xiong, L Hong, L Zheng, Y Wang, I King, ... arXiv preprint arXiv:2207.01586, 2022 | 49 | 2022 |
| Self-supervised contrastive learning for integrative single cell RNA-seq data analysis W Han, Y Cheng, J Chen, H Zhong, Z Hu, S Chen, L Zong, L Hong, ... Briefings in Bioinformatics 23 (5), bbac377, 2022 | 47 | 2022 |
| AcrNET: predicting anti-CRISPR with deep learning Y Li, Y Wei, S Xu, Q Tan, L Zong, J Wang, Y Wang, J Chen, L Hong, Y Li Bioinformatics 39 (5), btad259, 2023 | 10 | 2023 |
| Interpretable rna foundation model from unannotated data for highly accurate rna structure and function predictions. bioRxiv J Chen, Z Hu, S Sun, Q Tan, Y Wang, Q Yu, L Zong, L Hong, J Xiao, ... | 10 | 2022 |
| fastmsa: Accelerating multiple sequence alignment with dense retrieval on protein language L Hong, S Sun, L Zheng, Q Tan, Y Li bioRxiv, 2021.12. 20.473431, 2021 | 7 | 2021 |
| Fast, sensitive detection of protein homologs using deep dense retrieval L Hong, Z Hu, S Sun, X Tang, J Wang, Q Tan, L Zheng, S Wang, S Xu, ... Nature Biotechnology, 1-13, 2024 | 1 | 2024 |
| RiboDiffusion: tertiary structure-based RNA inverse folding with generative diffusion models H Huang, Z Lin, D He, L Hong, Y Li Bioinformatics 40 (Supplement_1), i347-i356, 2024 | 1 | 2024 |
Yu Li (李煜)Assistant Professor, Computer Science & Engineering, Chinese University of Hong KongVerified email at cse.cuhk.edu.hk
