| Predicting the clinical impact of human mutation with deep neural networks L Sundaram, H Gao, SR Padigepati, JF McRae, Y Li, JA Kosmicki, ... Nature genetics 50 (8), 1161-1170, 2018 | 363 | 2018 |
| DeepAtom: A framework for protein-ligand binding affinity prediction Y Li, MA Rezaei, C Li, X Li 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2019 | 105* | 2019 |
| Traffic engineering framework with machine learning based meta-layer in software-defined networks L Yanjun, L Xiaobo, Y Osamu 2014 4th IEEE International Conference on Network Infrastructure and Digital …, 2014 | 54 | 2014 |
| Analysis and visualization of spatial transcriptomic data B Liu, Y Li, L Zhang Frontiers in Genetics, 2022 | 35 | 2022 |
| Reinforcement learning in surgery S Datta, Y Li, MM Ruppert, Y Ren, B Shickel, T Ozrazgat-Baslanti, ... Surgery 170 (1), 329-332, 2021 | 29 | 2021 |
| Decision analysis and reinforcement learning in surgical decision-making TJ Loftus, AC Filiberto, Y Li, J Balch, AC Cook, PJ Tighe, PA Efron, ... Surgery 168 (2), 253-266, 2020 | 23 | 2020 |
| Foldingzero: Protein folding from scratch in hydrophobic-polar model Y Li, H Kang, K Ye, S Yin, X Li arXiv preprint arXiv:1812.00967, 2018 | 12 | 2018 |
| Improving the accuracy of protein-ligand binding affinity prediction by deep learning models: benchmark and model M Rezaei, Y Li, X Li, C Li | 9 | 2019 |
| DyScore: A Boosting Scoring Method with Dynamic Properties for Identifying True Binders and Non-binders in Structure-based Drug Discovery Y Li, D Zhou, G Zheng, X Li, D Wu, Y Yuan Journal of Chemical Information and Modeling, 2022 | 7 | 2022 |
| PRI-VAE: principle-of-Relevant-Information variational autoencoders Y Li, S Yu, JC Principe, X Li, D Wu arXiv preprint arXiv:2007.06503, 2020 | 7 | 2020 |
| Character sequence-to-sequence model with global attention for universal morphological reinflection Q Zhu, Y Li, X Li Proceedings of the CoNLL SIGMORPHON 2017 Shared Task: Universal …, 2017 | 5 | 2017 |
| BatmanNet: bi-branch masked graph transformer autoencoder for molecular representation Z Wang, Z Feng, Y Li, B Li, Y Wang, C Sha, M He, X Li Briefings in Bioinformatics 25 (1), bbad400, 2024 | 4 | 2024 |
| De novo design and optimization of aptamers with AptaDiff Z Wang, Z Liu, W Zhang, Y Li, Y Feng, S Lv, H Diao, Z Luo, P Yan, M He, ... bioRxiv, 2023.11. 25.568693, 2023 | 1 | 2023 |
| CRISPR-Cas9 Extracellular Vesicles for Treating Hearing Loss X Pan, P Huang, S Ali, TE Hutchinson, N Erwin, ZF Greenberg, Z Ding, ... bioRxiv, 2023.09. 14.557853, 2023 | 1 | 2023 |
| Physiologic signatures within six hours of hospitalization identify acute illness phenotypes Y Ren, TJ Loftus, Y Li, Z Guan, MM Ruppert, S Datta, GR Upchurch Jr., ... PLOS Digit Health, 2022 | 1 | 2022 |
| Phylogenetic-informed graph deep learning to classify dynamic transmission clusters in infectious disease epidemics C Sun, Y Li, S Marini, A Riva, DO Wu, M Salemi, BR Magalis bioRxiv, 2022.04. 10.487587, 2022 | 1 | 2022 |
| Identifying acute illness phenotypes via deep temporal interpolation and clustering network on physiologic signatures Y Ren, Y Li, TJ Loftus, J Balch, KL Abbott, MM Ruppert, Z Guan, B Shickel, ... Scientific Reports 14 (1), 8442, 2024 | | 2024 |
| Extracellular vesicles for developing targeted hearing loss therapy X Pan, Y Li, P Huang, H Staecker, M He Journal of Controlled Release 366, 460-478, 2024 | | 2024 |
| Morphological Profiling for Drug Discovery in the Era of Deep Learning Q Tang, R Ratnayake, G Seabra, Z Jiang, R Fang, L Cui, Y Ding, ... arXiv preprint arXiv:2312.07899, 2023 | | 2023 |
