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 | 117 | 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 | 67 | 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 | 64 | 2022 |
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, ... | 21 | 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 | 11 | 2023 |
Accurate RNA 3D structure prediction using a language model-based deep learning approach T Shen, Z Hu, S Sun, D Liu, F Wong, J Wang, J Chen, Y Wang, L Hong, ... Nature Methods, 1-12, 2024 | 9 | 2024 |
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 | 9 | 2021 |
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 | 8 | 2024 |
Deep generative design of RNA aptamers using structural predictions F Wong, D He, A Krishnan, L Hong, AZ Wang, J Wang, Z Hu, S Omori, A Li, ... Nature Computational Science, 1-11, 2024 | 6 | 2024 |
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 | 6 | 2024 |