| deepDR: a network-based deep learning approach to in silico drug repositioning X Zeng, S Zhu, X Liu, Y Zhou, R Nussinov, F Cheng Bioinformatics 35 (24), 5191-5198, 2019 | 409 | 2019 |
| Machine learning for drug-target interaction prediction R Chen, X Liu, S Jin, J Lin, J Liu Molecules 23 (9), 2208, 2018 | 258 | 2018 |
| Sequence clustering in bioinformatics: an empirical study Q Zou, G Lin, X Jiang, X Liu, X Zeng Briefings in bioinformatics 21 (1), 1-10, 2020 | 246 | 2020 |
| Application of machine learning in microbiology K Qu, F Guo, X Liu, Y Lin, Q Zou Frontiers in microbiology 10, 827, 2019 | 195 | 2019 |
| Hierarchical classification of protein folds using a novel ensemble classifier C Lin, Y Zou, J Qin, X Liu, Y Jiang, C Ke, Q Zou PloS one 8 (2), e56499, 2013 | 185 | 2013 |
| Application of deep learning methods in biological networks S Jin, X Zeng, F Xia, W Huang, X Liu Briefings in bioinformatics 22 (2), 1902-1917, 2021 | 163 | 2021 |
| Identifying enhancer–promoter interactions with neural network based on pre-trained DNA vectors and attention mechanism Z Hong, X Zeng, L Wei, X Liu Bioinformatics 36 (4), 1037-1043, 2020 | 149 | 2020 |
| Audio jack based miniaturized mobile phone electrochemical sensing platform X Wang, MR Gartia, J Jiang, TW Chang, J Qian, Y Liu, X Liu, GL Liu Sensors and actuators B: Chemical 209, 677-685, 2015 | 105 | 2015 |
| On languages generated by spiking neural P systems with weights X Zeng, L Xu, X Liu, L Pan Information Sciences 278, 423-433, 2014 | 93 | 2014 |
| Computational methods for identifying the critical nodes in biological networks X Liu, Z Hong, J Liu, Y Lin, A Rodríguez-Patón, Q Zou, X Zeng Briefings in bioinformatics 21 (2), 486-497, 2020 | 92 | 2020 |
| Asynchronous spiking neural P systems with rules on synapses T Song, Q Zou, X Liu, X Zeng Neurocomputing 151, 1439-1445, 2015 | 92 | 2015 |
| Aptamer-binding directed DNA origami pattern for logic gates J Yang, S Jiang, X Liu, L Pan, C Zhang ACS Applied Materials & Interfaces 8 (49), 34054-34060, 2016 | 76 | 2016 |
| A novel antibacterial peptide recognition algorithm based on BERT Y Zhang, J Lin, L Zhao, X Zeng, X Liu Briefings in bioinformatics 22 (6), bbab200, 2021 | 70 | 2021 |
| Exploratory predicting protein folding model with random forest and hybrid features X Zhao, Q Zou, B Liu, X Liu Current Proteomics 11 (4), 289-299, 2014 | 66 | 2014 |
| Implementation of arithmetic operations with time-free spiking neural P systems X Liu, Z Li, J Liu, L Liu, X Zeng IEEE Transactions on Nanobioscience 14 (6), 617-624, 2015 | 61 | 2015 |
| DeepTTA: a transformer-based model for predicting cancer drug response L Jiang, C Jiang, X Yu, R Fu, S Jin, X Liu Briefings in bioinformatics 23 (3), bbac100, 2022 | 60 | 2022 |
| An empirical study of features fusion techniques for protein-protein interaction prediction J Zeng, D Li, Y Wu, Q Zou, X Liu Current Bioinformatics 11 (1), 4-12, 2016 | 57 | 2016 |
| Identifying multi-functional enzyme by hierarchical multi-label classifier Q Zou, W Chen, Y Huang, X Liu, Y Jiang Journal of Computational and Theoretical Nanoscience 10 (4), 1038-1043, 2013 | 56 | 2013 |
| The challenges of explainable AI in biomedical data science H Han, X Liu BMC bioinformatics 22 (Suppl 12), 443, 2022 | 51 | 2022 |
| An advanced approach to identify antimicrobial peptides and their function types for penaeus through machine learning strategies Y Lin, Y Cai, J Liu, C Lin, X Liu BMC bioinformatics 20, 1-10, 2019 | 50 | 2019 |
Xiangxiang ZengDeparment of Computer Science, Hunan UniversityVerified email at hnu.edu.cn
