| A deep learning framework for modeling structural features of RNA-binding protein targets S Zhang, J Zhou, H Hu, H Gong, L Chen, C Cheng, J Zeng Nucleic acids research 44 (4), e32-e32, 2016 | 291 | 2016 |
| TITER: predicting translation initiation sites by deep learning S Zhang*, H Hu*, T Jiang, L Zhang, J Zeng Bioinformatics 33 (14), i234-i242, 2017 | 103 | 2017 |
| ACME: pan-specific peptide–MHC class I binding prediction through attention-based deep neural networks Y Hu, Z Wang, H Hu, F Wan, L Chen, Y Xiong, X Wang, D Zhao, W Huang, ... Bioinformatics 35 (23), 4946-4954, 2019 | 75 | 2019 |
| DeepCPI: a deep learning-based framework for large-scale in silico drug screening F Wan*, Y Zhu*, H Hu*, A Dai, X Cai, L Chen, H Gong, T Xia, D Yang, ... Genomics, proteomics & bioinformatics 17 (5), 478-495, 2019 | 73 | 2019 |
| Analysis of ribosome stalling and translation elongation dynamics by deep learning S Zhang*, H Hu*, J Zhou*, X He, T Jiang, J Zeng Cell systems 5 (3), 212-220. e6, 2017 | 66 | 2017 |
| Crowdsourced mapping of unexplored target space of kinase inhibitors A Cichońska, B Ravikumar, RJ Allaway, F Wan, S Park, O Isayev, S Li, ... Nature communications 12 (1), 3307, 2021 | 62 | 2021 |
| Inhibitor discovery for the human GLUT1 from homology modeling and virtual screening PMU Ung, W Song, L Cheng, X Zhao, H Hu, L Chen, A Schlessinger ACS chemical biology 11 (7), 1908-1916, 2016 | 60 | 2016 |
| Reconstructing spatial organizations of chromosomes through manifold learning G Zhu, W Deng, H Hu, R Ma, S Zhang, J Yang, J Peng, T Kaplan, J Zeng Nucleic acids research 46 (8), e50-e50, 2018 | 59 | 2018 |
| DeepHINT: understanding HIV-1 integration via deep learning with attention H Hu, A Xiao, S Zhang, Y Li, X Shi, T Jiang, L Zhang, L Zhang, J Zeng Bioinformatics 35 (10), 1660-1667, 2019 | 57 | 2019 |
| SNAC-tag for sequence-specific chemical protein cleavage B Dang, M Mravic, H Hu, N Schmidt, B Mensa, WF DeGrado Nature methods 16 (4), 319-322, 2019 | 42 | 2019 |
| DATSING: Data augmented time series forecasting with adversarial domain adaptation H Hu, MJ Tang, C Bai Proceedings of the 29th ACM International Conference on Information …, 2020 | 27 | 2020 |
| Secure multiparty computation for privacy-preserving drug discovery R Ma, Y Li, C Li, F Wan, H Hu, W Xu, J Zeng Bioinformatics 36 (9), 2872-2880, 2020 | 24 | 2020 |
| How Well Does Self-Supervised Pre-Training Perform with Streaming Data? D Hu, S Yan, Q Lu, L Hong, H Hu, Y Zhang, Z Li, X Wang, J Feng International Conference on Learning Representations (ICLR), 2022 | 21 | 2022 |
| DensE: An enhanced non-commutative representation for knowledge graph embedding with adaptive semantic hierarchy H Lu, H Hu, X Lin Neurocomputing 476, 115-125, 2022 | 20 | 2022 |
| Genimage: A million-scale benchmark for detecting ai-generated image M Zhu, H Chen, Q Yan, X Huang, G Lin, W Li, Z Tu, H Hu, J Hu, Y Wang Advances in Neural Information Processing Systems 36, 2024 | 19 | 2024 |
| De novo designed transmembrane peptides activating the α5β1 integrin M Mravic*, H Hu*, Z Lu, JS Bennett, CR Sanders, AW Orr, WF DeGrado Protein Engineering, Design and Selection 31 (5), 181-190, 2018 | 17 | 2018 |
| ROSE: a deep learning based framework for predicting ribosome stalling S Zhang*, H Hu*, J Zhou*, X He, T Jiang, J Zeng Proceedings of the 21st Annual International Conference on Research in …, 2017 | 15 | 2017 |
| Evaluation of work resumption strategies after COVID-19 reopening in the Chinese city of Shenzhen: a mathematical modeling study L Bai, H Lu, H Hu, MK Smith, K Harripersaud, V Lipkova, Y Wen, X Guo, ... Public Health 193, 17-22, 2021 | 14 | 2021 |
| DensE: An enhanced non-abelian group representation for knowledge graph embedding H Lu, H Hu arXiv preprint arXiv:2008.04548, 2020 | 14 | 2020 |
| Less is more: Focus attention for efficient DETR D Zheng, W Dong, H Hu, X Chen, Y Wang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 13 | 2023 |
Sai ZhangAssistant Professor, University of FloridaE-mail megerősítve itt: ufl.edu
