| Cross-dependent graph neural networks for molecular property prediction H Ma, Y Bian, Y Rong, W Huang, T Xu, W Xie, G Ye, J Huang Bioinformatics 38 (7), 2003-2009, 2022 | 91* | 2022 |
| Exploring robustness of unsupervised domain adaptation in semantic segmentation J Yang, C Li, W An, H Ma, Y Guo, Y Rong, P Zhao, J Huang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 35 | 2021 |
| Hierarchical graph capsule network J Yang, P Zhao, Y Rong, C Yan, C Li, H Ma, J Huang Proceedings of the AAAI Conference on Artificial Intelligence 35 (12), 10603 …, 2021 | 34 | 2021 |
| Self-supervised pre-training for protein embeddings using tertiary structures Y Guo, J Wu, H Ma, J Huang Proceedings of the AAAI conference on artificial intelligence 36 (6), 6801-6809, 2022 | 24 | 2022 |
| Chatgraph: Interpretable text classification by converting chatgpt knowledge to graphs Y Shi, H Ma, W Zhong, Q Tan, G Mai, X Li, T Liu, J Huang 2023 IEEE International Conference on Data Mining Workshops (ICDMW), 515-520, 2023 | 22 | 2023 |
| Deep graph learning with property augmentation for predicting drug-induced liver injury H Ma, W An, Y Wang, H Sun, R Huang, J Huang Chemical research in toxicology 34 (2), 495-506, 2020 | 21 | 2020 |
| Bagging msa learning: Enhancing low-quality pssm with deep learning for accurate protein structure property prediction Y Guo, J Wu, H Ma, S Wang, J Huang Research in Computational Molecular Biology: 24th Annual International …, 2020 | 20 | 2020 |
| EPTool: a new enhancing PSSM tool for protein secondary structure prediction Y Guo, J Wu, H Ma, S Wang, J Huang Journal of Computational Biology 28 (4), 362-364, 2021 | 12 | 2021 |
| MoDNA: motif-oriented pre-training for DNA language model W An, Y Guo, Y Bian, H Ma, J Yang, C Li, J Huang Proceedings of the 13th ACM International Conference on Bioinformatics …, 2022 | 9 | 2022 |
| Graph Neural Networks: Scalability H Ma, Y Rong, J Huang Graph Neural Networks: Foundations, Frontiers, and Applications, 99-119, 2022 | 9 | 2022 |
| Improving molecular property prediction on limited data with deep multi-label learning H Ma, C Yan, Y Guo, S Wang, Y Wang, H Sun, J Huang 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2020 | 8 | 2020 |
| Protein ensemble learning with atrous spatial pyramid networks for secondary structure prediction Y Guo, J Wu, H Ma, S Wang, J Huang 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2020 | 8 | 2020 |
| Robust self-training strategy for various molecular biology prediction tasks H Ma, F Jiang, Y Rong, Y Guo, J Huang Proceedings of the 13th ACM International Conference on Bioinformatics …, 2022 | 6 | 2022 |
| Comprehensive study on enhancing low-quality position-specific scoring matrix with deep learning for accurate protein structure property prediction: using bagging multiple … Y Guo, J Wu, H Ma, S Wang, J Huang Journal of Computational Biology 28 (4), 346-361, 2021 | 6 | 2021 |
| Deep ensemble learning with atrous spatial pyramid networks for protein secondary structure prediction Y Guo, J Wu, H Ma, S Wang, J Huang Biomolecules 12 (6), 774, 2022 | 5 | 2022 |
| Gradient-norm based attentive loss for molecular property prediction H Ma, Y Rong, B Liu, Y Guo, C Yan, J Huang 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2021 | 5 | 2021 |
| Recent advances in toxicity prediction: Applications of deep graph learning Y Miao, H Ma, J Huang Chemical Research in Toxicology 36 (8), 1206-1226, 2023 | 4 | 2023 |
| NuSegDA: domain adaptation for nuclei segmentation MM Haq, H Ma, J Huang Frontiers in Big Data 6, 1108659, 2023 | 4 | 2023 |
| Weightaln: Weighted homologous alignment for protein structure property prediction Y Guo, J Wu, H Ma, J Yang, X Zhu, J Huang 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2020 | 4 | 2020 |
| Molecule sequence generation with rebalanced variational autoencoder loss C Yan, J Yang, H Ma, S Wang, J Huang Journal of Computational Biology 30 (1), 82-94, 2023 | 3 | 2023 |
