| Tensor decomposition with relational constraints for predicting multiple types of microRNA-disease associations F Huang, X Yue, Z Xiong, Z Yu, S Liu, W Zhang Briefings in bioinformatics 22 (3), bbaa140, 2021 | 61 | 2021 |
| A heterogeneous network-based method with attentive meta-path extraction for predicting drug–target interactions H Wang, F Huang, Z Xiong, W Zhang Briefings in Bioinformatics 23 (4), bbac184, 2022 | 24 | 2022 |
| A Multimodal Framework for Improving in Silico Drug Repositioning With the Prior Knowledge From Knowledge Graphs Z Xiong, F Huang, Z Wang, S Liu, W Zhang IEEE/ACM Transactions on Computational Biology and Bioinformatics 19 (5 …, 2021 | 16 | 2021 |
| Multi-relational contrastive learning graph neural network for drug-drug interaction event prediction Z Xiong, S Liu, F Huang, Z Wang, X Liu, Z Zhang, W Zhang Proceedings of the AAAI Conference on Artificial Intelligence 37 (4), 5339-5347, 2023 | 9 | 2023 |
| Multi-view contrastive learning hypergraph neural network for drug-microbe-disease association prediction L Liu, F Huang, X Liu, Z Xiong, M Li, C Song, W Zhang Proceedings of the Thirty-Second International Joint Conference on …, 2023 | 2 | 2023 |
| A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide Generation Y Wang, X Liu, F Huang, Z Xiong, W Zhang Proceedings of the AAAI Conference on Artificial Intelligence 38 (1), 3-11, 2024 | | 2024 |
| Deep learning for drug‐drug interaction prediction: A comprehensive review X Li, Z Xiong, W Zhang, S Liu Quantitative Biology, 2024 | | 2024 |
| Evolution-strengthened knowledge graph enables predicting the targetability and druggability of genes Y Quan, ZK Xiong, KX Zhang, QY Zhang, W Zhang, HY Zhang PNAS nexus 2 (5), pgad147, 2023 | | 2023 |
| Predicting drug transcriptional response similarity using Signed Graph Convolutional Network Z Wang, C Hong, X Liu, Z Xiong, F Liu, W Zhang 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2022 | | 2022 |
| Predicting microRNA-disease associations from knowledge graph using tensor decomposition with relational constraints. F Huang, Z Xiong, G Zhang, Z Yu, X Xu, W Zhang CoRR, 2019 | | 2019 |
