| Application of deep learning in microbiome Q Zhu, B Huo, H Sun, B Li, X Jiang Journal of Artificial Intelligence for Medical Sciences 1 (1-2), 23-29, 2020 | 5 | 2020 |
| Detecting sparse microbial association signals adaptively from longitudinal microbiome data based on generalized estimating equations H Sun, X Huang, B Huo, Y Tan, T He, X Jiang Briefings in Bioinformatics 23 (5), bbac149, 2022 | 4 | 2022 |
| An Effective Model for Predicting Phage-Host Interactions Via Graph Embedding Representation Learning With Multi-Head Attention Mechanism Y Wang, H Sun, H Wang, D Li, W Zhao, X Jiang, X Shen IEEE Journal of Biomedical and Health Informatics, 2023 | 2 | 2023 |
| A powerful adaptive microbiome-based association test for microbial association signals with diverse sparsity levels H Sun, X Huang, L Fu, B Huo, T He, X Jiang Journal of Genetics and Genomics 48 (9), 851-859, 2021 | 2 | 2021 |
| Prediction of Drug–disease Associations Based on Multi-kernel Deep Learning Method in Heterogeneous Graph Embedding D Li, Z Xiao, H Sun, X Jiang, W Zhao, X Shen IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023 | 1 | 2023 |
| A Simplex Hypergraph Clustering Method for Detecting Higher-order Modules in Microbial Network R Xiang, L Fu, Y Wang, H Sun, X Shen 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2021 | 1 | 2021 |
| multiMiAT: an optimal microbiome-based association test for multicategory phenotypes H Sun, Y Wang, Z Xiao, X Huang, H Wang, T He, X Jiang Briefings in Bioinformatics 24 (2), bbad012, 2023 | | 2023 |
| Predicting human microbe-disease associations based on multi-source heterogeneous graph representation learning model H Wang, H Sun, Y Wang, W Zhao, X Jiang, X Shen 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2022 | | 2022 |
