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 | 376 | 2019 |
Machine learning for drug-target interaction prediction R Chen, X Liu, S Jin, J Lin, J Liu Molecules 23 (9), 2208, 2018 | 238 | 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 | 228 | 2020 |
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 | 182 | 2013 |
Application of machine learning in microbiology K Qu, F Guo, X Liu, Y Lin, Q Zou Frontiers in microbiology 10, 451710, 2019 | 174 | 2019 |
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 | 139 | 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 | 138 | 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 | 102 | 2015 |
Asynchronous spiking neural P systems with rules on synapses T Song, Q Zou, X Liu, X Zeng Neurocomputing 151, 1439-1445, 2015 | 92 | 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 | 92 | 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 | 85 | 2020 |
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 | 73 | 2016 |
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 | 65 | 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 |
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 |
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 | 55 | 2021 |
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 | 55 | 2013 |
imDC: an ensemble learning method for imbalanced classification with miRNA data CY Wang, L Hu, MZ Guo, XY Liu, Q Zou Genetics and Molecular Research 14 (1), 123-133, 2015 | 49 | 2015 |
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 | 44 | 2019 |
The challenges of explainable AI in biomedical data science H Han, X Liu BMC bioinformatics 22 (Suppl 12), 443, 2022 | 41 | 2022 |