| The lncLocator: a subcellular localization predictor for long non-coding RNAs based on a stacked ensemble classifier Z Cao, X Pan, Y Yang, Y Huang, HB Shen Bioinformatics 34 (13), 2185-2194, 2018 | 346 | 2018 |
| Roles of small RNAs in soybean defense against Phytophthora sojae infection. J Wong, L Gao, Y Yang, J Zhai, S Arikit, Y Yu, SD al. the plant journal 79 (6), 2014 | 149 | 2014 |
| Accelerating materials discovery using machine learning Y Juan, Y Dai, Y Yang, J Zhang Journal of Materials Science & Technology 79, 178-190, 2021 | 117 | 2021 |
| Hum-mPLoc 3.0: prediction enhancement of human protein subcellular localization through modeling the hidden correlations of gene ontology and functional domain features H Zhou, Y Yang, HB Shen Bioinformatics 33 (6), 843-853, 2017 | 105 | 2017 |
| Computational prediction of type III secreted proteins from gram-negative bacteria Y Yang, J Zhao, RL Morgan, W Ma, T Jiang BMC bioinformatics 11 (Suppl 1), S47, 2010 | 91 | 2010 |
| CRIP: predicting circRNA–RBP-binding sites using a codon-based encoding and hybrid deep neural networks K Zhang, X Pan, Y Yang, HB Shen Rna 25 (12), 1604-1615, 2019 | 70 | 2019 |
| Recent methodology progress of deep learning for RNA–protein interaction prediction X Pan, Y Yang, CQ Xia, AH Mirza, HB Shen Wiley Interdisciplinary Reviews: RNA 10 (6), e1544, 2019 | 64 | 2019 |
| MiRGOFS: a GO-based functional similarity measurement for miRNAs, with applications to the prediction of miRNA subcellular localization and miRNA–disease association Y Yang, X Fu, W Qu, Y Xiao, HB Shen Bioinformatics 34 (20), 3547-3556, 2018 | 53 | 2018 |
| Computational prediction of novel non-coding RNAs in Arabidopsis thaliana D Song, Y Yang, B Yu, B Zheng, Z Deng, BL Lu, X Chen, T Jiang BMC Bioinformatics 10, 2009 | 52 | 2009 |
| RBPsuite: RNA-protein binding sites prediction suite based on deep learning X Pan, Y Fang, X Li, Y Yang, HB Shen BMC genomics 21, 1-8, 2020 | 51 | 2020 |
| Predicting gene regulatory interactions based on spatial gene expression data and deep learning Y Yang, Q Fang, HB Shen PLoS computational biology 15 (9), e1007324, 2019 | 47 | 2019 |
| Protein subcellular multi-localization prediction using a min-max modular support vector machine Y Yang, BL Lu International Journal of Neural Systems 20 (1), 13-28, 2010 | 44 | 2010 |
| ImPLoc: a multi-instance deep learning model for the prediction of protein subcellular localization based on immunohistochemistry images W Long, Y Yang, HB Shen Bioinformatics 36 (7), 2244-2250, 2020 | 43 | 2020 |
| CircSLNN: identifying RBP-binding sites on circRNAs via sequence labeling neural networks Y Ju, L Yuan, Y Yang, H Zhao Frontiers in genetics, 1184, 2019 | 39 | 2019 |
| MemBrain: an easy-to-use online webserver for transmembrane protein structure prediction X Yin, J Yang, F Xiao, Y Yang, HB Shen Nano-Micro Letters 10, 1-8, 2018 | 39 | 2018 |
| Missing value imputation for microRNA expression data by using a GO-based similarity measure Y Yang, Z Xu, D Song BMC bioinformatics 17 (1), 109-116, 2016 | 35 | 2016 |
| Interplay of Metabolome and Gut Microbiome in Individuals With Major Depressive Disorder vs Control Individuals N Amin, J Liu, B Bonnechere, S MahmoudianDehkordi, M Arnold, R Batra, ... JAMA psychiatry, 2023 | 34 | 2023 |
| A clustering-based approach for efficient identification of microRNA combinatorial biomarkers Y Yang, N Huang, L Hao, W Kong BMC genomics 18 (2), 1-14, 2017 | 33 | 2017 |
| Artificial intelligence-based multi-objective optimization protocol for protein structure refinement D Wang, L Geng, YJ Zhao, Y Yang, Y Huang, Y Zhang, HB Shen Bioinformatics 36 (2), 437-448, 2020 | 30 | 2020 |
| Topology prediction improvement of α-helical transmembrane proteins through helix-tail modeling and multiscale deep learning fusion SH Feng, WX Zhang, J Yang, Y Yang, HB Shen Journal of Molecular Biology, 2020 | 30 | 2020 |
