| CarcinoPred-EL: Novel models for predicting the carcinogenicity of chemicals using molecular fingerprints and ensemble learning methods L Zhang, H Ai, W Chen, Z Yin, H Hu, J Zhu, J Zhao, Q Zhao, H Liu Scientific reports 7 (1), 2118, 2017 | 213 | 2017 |
| The exopolysaccharide Psl–eDNA interaction enables the formation of a biofilm skeleton in Pseudomonas aeruginosa S Wang, X Liu, H Liu, L Zhang, Y Guo, S Yu, DJ Wozniak, LZ Ma Environmental microbiology reports 7 (2), 330-340, 2015 | 168 | 2015 |
| Using network distance analysis to predict lncRNA–miRNA interactions L Zhang, P Yang, H Feng, Q Zhao, H Liu Interdisciplinary sciences: computational life sciences 13, 535-545, 2021 | 162 | 2021 |
| Antiviral effects of two Ganoderma lucidum triterpenoids against enterovirus 71 infection W Zhang, J Tao, X Yang, Z Yang, L Zhang, H Liu, K Wu, J Wu Biochemical and biophysical research communications 449 (3), 307-312, 2014 | 144 | 2014 |
| Biological synthesis of high-conductive pili in aerobic bacterium Pseudomonas aeruginosa X Liu, S Wang, A Xu, L Zhang, H Liu, LZ Ma Applied microbiology and biotechnology 103, 1535-1544, 2019 | 106 | 2019 |
| HLPI-Ensemble: Prediction of human lncRNA-protein interactions based on ensemble strategy H Hu, L Zhang, H Ai, H Zhang, Y Fan, Q Zhao, H Liu RNA biology 15 (6), 797-806, 2018 | 105 | 2018 |
| Applications of machine learning methods in drug toxicity prediction L Zhang, H Zhang, H Ai, H Hu, S Li, J Zhao, H Liu Current topics in medicinal chemistry 18 (12), 987-997, 2018 | 105 | 2018 |
| Predicting drug-induced liver injury using ensemble learning methods and molecular fingerprints H Ai, W Chen, L Zhang, L Huang, Z Yin, H Hu, Q Zhao, J Zhao, H Liu Toxicological Sciences 165 (1), 100-107, 2018 | 82 | 2018 |
| DCAMCP: A deep learning model based on capsule network and attention mechanism for molecular carcinogenicity prediction Z Chen, L Zhang, J Sun, R Meng, S Yin, Q Zhao Journal of cellular and molecular medicine 27 (20), 3117-3126, 2023 | 78 | 2023 |
| Predicting lncRNA–miRNA interactions based on interactome network and graphlet interaction L Zhang, T Liu, H Chen, Q Zhao, H Liu Genomics 113 (3), 874-880, 2021 | 75 | 2021 |
| Prediction of potential miRNA–disease associations through a novel unsupervised deep learning framework with variational autoencoder L Zhang, X Chen, J Yin Cells 8 (9), 1040, 2019 | 72 | 2019 |
| LPI-ETSLP: lncRNA–protein interaction prediction using eigenvalue transformation-based semi-supervised link prediction H Hu, C Zhu, H Ai, L Zhang, J Zhao, Q Zhao, H Liu Molecular BioSystems 13 (9), 1781-1787, 2017 | 70 | 2017 |
| QSAR modelling study of the bioconcentration factor and toxicity of organic compounds to aquatic organisms using machine learning and ensemble methods H Ai, X Wu, L Zhang, M Qi, Y Zhao, Q Zhao, J Zhao, H Liu Ecotoxicology and environmental safety 179, 71-78, 2019 | 69 | 2019 |
| Prediction of the blood–brain barrier (BBB) permeability of chemicals based on machine-learning and ensemble methods L Liu, L Zhang, H Feng, S Li, M Liu, J Zhao, H Liu Chemical Research in Toxicology 34 (6), 1456-1467, 2021 | 67 | 2021 |
| Virtual screening approach to identifying influenza virus neuraminidase inhibitors using molecular docking combined with machine-learning-based scoring function L Zhang, HX Ai, SM Li, MY Qi, J Zhao, Q Zhao, HS Liu Oncotarget 8 (47), 83142, 2017 | 57 | 2017 |
| Study on the interaction of paeoniflorin with human serum albumin (HSA) by spectroscopic and molecular docking techniques L Xu, YX Hu, YC Li, YF Liu, L Zhang, HX Ai, HS Liu Chemistry Central Journal 11, 1-12, 2017 | 46 | 2017 |
| Predicting the reproductive toxicity of chemicals using ensemble learning methods and molecular fingerprints H Feng, L Zhang, S Li, L Liu, T Yang, P Yang, J Zhao, IT Arkin, H Liu Toxicology Letters 340, 4-14, 2021 | 42 | 2021 |
| LPI-NRLMF: lncRNA-protein interaction prediction by neighborhood regularized logistic matrix factorization H Liu, G Ren, H Hu, L Zhang, H Ai, W Zhang, Q Zhao Oncotarget 8 (61), 103975, 2017 | 42 | 2017 |
| Predicting drug-induced liver injury using graph attention mechanism and molecular fingerprints J Wang, L Zhang, J Sun, X Yang, W Wu, W Chen, Q Zhao Methods 221, 18-26, 2024 | 36 | 2024 |
| MutagenPred-GCNNs: a graph convolutional neural network-based classification model for mutagenicity prediction with data-driven molecular fingerprints S Li, L Zhang, H Feng, J Meng, D Xie, L Yi, IT Arkin, H Liu Interdisciplinary Sciences: Computational Life Sciences 13, 25-33, 2021 | 33 | 2021 |
