| iPro-WAEL: a comprehensive and robust framework for identifying promoters in multiple species P Zhang, H Zhang, H Wu Nucleic Acids Research 50 (18), 10278-10289, 2022 | 48 | 2022 |
| CLNN-loop: a deep learning model to predict CTCF-mediated chromatin loops in the different cell lines and CTCF-binding sites (CBS) pair types P Zhang, Y Wu, H Zhou, B Zhou, H Zhang, H Wu Bioinformatics 38 (19), 4497-4504, 2022 | 40 | 2022 |
| IChrom-deep: an attention-based deep learning model for identifying chromatin interactions P Zhang, H Wu IEEE Journal of Biomedical and Health Informatics, 2023 | 24 | 2023 |
| StackTADB: a stacking-based ensemble learning model for predicting the boundaries of topologically associating domains (TADs) accurately in fruit flies H Wu, P Zhang, Z Ai, L Wei, H Zhang, F Yang, L Cui Briefings in Bioinformatics 23 (2), bbac023, 2022 | 12 | 2022 |
| iEnhancer-SKNN: a stacking ensemble learning-based method for enhancer identification and classification using sequence information H Wu, M Liu, P Zhang, H Zhang Briefings in Functional Genomics 22 (3), 302-311, 2023 | 7 | 2023 |
| Enhancer-MDLF: a novel deep learning framework for identifying cell-specific enhancers Y Zhang, P Zhang, H Wu Briefings in Bioinformatics 25 (2), bbae083, 2024 | 5 | 2024 |
| Be-1DCNN: a neural network model for chromatin loop prediction based on bagging ensemble learning H Wu, B Zhou, H Zhou, P Zhang, M Wang Briefings in Functional Genomics 22 (5), 475-484, 2023 | 2 | 2023 |
| scHiCyclePred: a deep learning framework for predicting cell cycle phases from single-cell Hi-C data using multi-scale interaction information Y Wu, Z Shi, X Zhou, P Zhang, X Yang, J Ding, H Wu Communications Biology 7 (1), 923, 2024 | | 2024 |
