| Predicting diabetes mellitus with machine learning techniques Q Zou, K Qu, Y Luo, D Yin, Y Ju, H Tang Frontiers in genetics 9, 515, 2018 | 919 | 2018 |
| Distance-based support vector machine to predict DNA N6-methyladenine modification H Zhang, Q Zou, Y Ju, C Song, D Chen Current Bioinformatics 17 (5), 473-482, 2022 | 312 | 2022 |
| Finding the best classification threshold in imbalanced classification Q Zou, S Xie, Z Lin, M Wu, Y Ju Big Data Research 5, 2-8, 2016 | 292 | 2016 |
| Prediction of MicroRNA‐disease associations based on social network analysis methods Q Zou, J Li, Q Hong, Z Lin, Y Wu, H Shi, Y Ju BioMed research international 2015 (1), 810514, 2015 | 169 | 2015 |
| Pretata: predicting TATA binding proteins with novel features and dimensionality reduction strategy Q Zou, S Wan, Y Ju, J Tang, X Zeng BMC systems biology 10, 401-412, 2016 | 164 | 2016 |
| Protein folds prediction with hierarchical structured SVM D Li, Y Ju, Q Zou Current Proteomics 13 (2), 79-85, 2016 | 129 | 2016 |
| Improving tRNAscan‐SE annotation results via ensemble classifiers Q Zou, J Guo, Y Ju, M Wu, X Zeng, Z Hong Molecular informatics 34 (11‐12), 761-770, 2015 | 66 | 2015 |
| Human protein subcellular localization with integrated source and multi-label ensemble classifier X Guo, F Liu, Y Ju, Z Wang, C Wang Scientific Reports 6 (1), 28087, 2016 | 63 | 2016 |
| Prediction of G protein‐coupled receptors with SVM‐prot features and random forest Z Liao, Y Ju, Q Zou Scientifica 2016 (1), 8309253, 2016 | 59 | 2016 |
| Dual mutual learning for cross-modality person re-identification D Zhang, Z Zhang, Y Ju, C Wang, Y Xie, Y Qu IEEE Transactions on Circuits and Systems for Video Technology 32 (8), 5361-5373, 2022 | 56 | 2022 |
| In Silico Prediction of Gamma‐Aminobutyric Acid Type‐A Receptors Using Novel Machine‐Learning‐Based SVM and GBDT Approaches Z Liao, Y Huang, X Yue, H Lu, P Xuan, Y Ju BioMed research international 2016 (1), 2375268, 2016 | 46 | 2016 |
| Complex network clustering by a multi-objective evolutionary algorithm based on decomposition and membrane structure Y Ju, S Zhang, N Ding, X Zeng, X Zhang Scientific reports 6 (1), 33870, 2016 | 39 | 2016 |
| Review of protein subcellular localization prediction Z Wang, Q Zou, Y Jiang, Y Ju, X Zeng Current Bioinformatics 9 (3), 331-342, 2014 | 39 | 2014 |
| DeepAc4C: a convolutional neural network model with hybrid features composed of physicochemical patterns and distributed representation information for identification of N4 … C Wang, Y Ju, Q Zou, C Lin Bioinformatics 38 (1), 52-57, 2022 | 34 | 2022 |
| Accurate identification of cancerlectins through hybrid machine learning technology J Zhang, Y Ju, H Lu, P Xuan, Q Zou International journal of genomics 2016 (1), 7604641, 2016 | 34 | 2016 |
| Identification of multi-functional enzyme with multi-label classifier Y Che, Y Ju, P Xuan, R Long, F Xing PloS one 11 (4), e0153503, 2016 | 30 | 2016 |
| 基于最小二乘法的网络借贷模型 吴小英， 鞠颖 厦门大学学报: 自然科学版 51 (6), 980-984, 2012 | 22 | 2012 |
| Characterizing viral circRNAs and their application in identifying circRNAs in viruses M Niu, Y Ju, C Lin, Q Zou Briefings in Bioinformatics 23 (1), bbab404, 2022 | 21 | 2022 |
| Sc-ncDNAPred: A Sequence-Based Predictor for Identifying Non-coding DNA in Saccharomyces cerevisiae W He, Y Ju, X Zeng, X Liu, Q Zou Frontiers in microbiology 9, 2174, 2018 | 19 | 2018 |
| A fast method to segment the liver according to Couinaud’s classification S Huang, B Wang, M Cheng, W Wu, X Huang, Y Ju Medical Imaging and Informatics: 2nd International Conference, MIMI 2007 …, 2008 | 18 | 2008 |
