| Deep learning methods for protein torsion angle prediction H Li, J Hou, B Adhikari, Q Lyu, J Cheng BMC bioinformatics 18, 1-13, 2017 | 65 | 2017 |
| Predicting RNA secondary structure via adaptive deep recurrent neural networks with energy-based filter W Lu, Y Tang, H Wu, H Huang, Q Fu, J Qiu, H Li BMC bioinformatics 20, 1-10, 2019 | 34 | 2019 |
| A template-based protein structure reconstruction method using deep autoencoder learning H Li, Q Lyu, J Cheng Journal of proteomics & bioinformatics 9 (12), 306, 2016 | 16 | 2016 |
| PaFlexPepDock: Parallel Ab-Initio Docking of Peptides onto Their Receptors with Full Flexibility Based on Rosetta QL Haiou Li, Liyao Lu, Rong Chen, Lijun Quan, Xiaoyan Xia PLOS ONE 9 (5), e94769, 2014 | 15 | 2014 |
| Empirical potential energy function toward ab initio folding G protein-coupled receptors H Wu, H Ling, L Gao, Q Fu, W Lu, Y Ding, M Jiang, H Li IEEE/ACM Transactions on Computational Biology and Bioinformatics 18 (5 …, 2020 | 13 | 2020 |
| Identify High‐Quality Protein Structural Models by Enhanced K‐Means H Wu, H Li, M Jiang, C Chen, Q Lv, C Wu BioMed Research International 2017 (1), 7294519, 2017 | 13 | 2017 |
| Research on predicting 2D-HP protein folding using reinforcement learning with full state space H Wu, R Yang, Q Fu, J Chen, W Lu, H Li BMC bioinformatics 20, 1-11, 2019 | 12 | 2019 |
| Use Chou’s 5‐Step Rule to Predict DNA‐Binding Proteins with Evolutionary Information W Lu, Z Song, Y Ding, H Wu, Y Cao, Y Zhang, H Li BioMed Research International 2020 (1), 6984045, 2020 | 10 | 2020 |
| Research on RNA secondary structure predicting via bidirectional recurrent neural network W Lu, Y Cao, H Wu, Y Ding, Z Song, Y Zhang, Q Fu, H Li BMC bioinformatics 22, 1-18, 2021 | 9 | 2021 |
| Ranking near-native candidate protein structures via random forest classification H Wu, H Huang, W Lu, Q Fu, Y Ding, J Qiu, H Li BMC bioinformatics 20, 1-13, 2019 | 7 | 2019 |
| Improved packing of protein side chains with parallel ant colonies et al. Quan L, Lü Q, Li H BMC bioinformatics 15 (S5), 2014 | 7 | 2014 |
| Application of DNA‐Binding Protein Prediction Based on Graph Convolutional Network and Contact Map W Lu, N Zhou, Y Ding, H Wu, Y Zhang, Q Fu, H Li BioMed Research International 2022 (1), 9044793, 2022 | 4 | 2022 |
| Identification of Membrane Protein Types Based Using Hypergraph Neural Network W Lu, M Qian, Y Zhang, H Wu, Y Ding, J Shen, X Chen, H Li, Q Fu Current Bioinformatics 18 (4), 346-358, 2023 | 2 | 2023 |
| DNA-binding protein prediction based on deep learning feature fusion S Guan, T Jiang, W Lu, Q Fu, H Li, H Wu Intelligent Computing Theories and Application: 17th International …, 2021 | 2 | 2021 |
| GPCR 跨膜螺旋的结构拓扑建模及其预测方法 吴宏杰， 吕强， 权丽君， 陈荣， 陈沙沙， 李海鸥， 钱培德 计算机学报 36 (10), 2168-2178, 2013 | 2 | 2013 |
| Transformer and Graph Transformer-Based Prediction of Drug-Target Interactions M Qian, W Lu, Y Zhang, J Liu, H Wu, Y Lu, H Li, Q Fu, J Shen, Y Xiao Current Bioinformatics 19 (5), 470-481, 2024 | | 2024 |
| Modeling Protein Loop Structure by Cyclic Coordinate Descent-based Approach et al. Li H, Sun L, Luo S Journal of Computational Biology 23 (2), 123-136, 2016 | | 2016 |
