| Pan-peptide meta learning for T-cell receptor–antigen binding recognition Y Gao, Y Gao, Y Fan, C Zhu, Z Wei, C Zhou, G Chuai, Q Chen, H Zhang, ... Nature Machine Intelligence 5 (3), 236-249, 2023 | 52 | 2023 |
| Data imbalance in CRISPR off-target prediction Y Gao, G Chuai, W Yu, S Qu, Q Liu Briefings in bioinformatics 21 (4), 1448-1454, 2020 | 27 | 2020 |
| Benchmarking and integrating genome-wide CRISPR off-target detection and prediction J Yan, D Xue, G Chuai, Y Gao, G Zhang, Q Liu Nucleic acids research 48 (20), 11370-11379, 2020 | 18 | 2020 |
| Reply to: The pitfalls of negative data bias for the T-cell epitope specificity challenge Y Gao, Y Gao, K Dong, S Wu, Q Liu Nature Machine Intelligence 5 (10), 1063-1065, 2023 | 15 | 2023 |
| iDMer: an integrative and mechanism-driven response system for identifying compound interventions for sudden virus outbreak Z Wei, Y Gao, F Meng, X Chen, Y Gong, C Zhu, B Ju, C Zhang, Z Liu, ... Briefings in bioinformatics 22 (2), 976-987, 2021 | 7 | 2021 |
| Neo-epitope identification by weakly-supervised peptide-TCR binding prediction Y Gao, Y Gao, W Li, S Wu, F Xing, C Zhou, S Fu, G Chuai, Q Chen, ... bioRxiv, 2023.08. 02.550128, 2023 | 2 | 2023 |
| Unified cross-modality integration and analysis of T cell receptors and T cell transcriptomes by low-resource-aware representation learning Y Gao, K Dong, Y Gao, X Jin, J Yang, G Yan, Q Liu Cell Genomics 4 (5), 2024 | | 2024 |
| Unified cross-modality integration and analysis of T-cell receptors and T-cell transcriptomes Y Gao, K Dong, Y Gao, X Jin, Q Liu bioRxiv, 2023.08. 19.553790, 2023 | | 2023 |
