| Predicting DNA methylation state of CpG dinucleotide using genome topological features and deep networks Y Wang, T Liu, D Xu, H Shi, C Zhang, YY Mo, Z Wang Scientific reports 6 (1), 19598, 2016 | 104 | 2016 |
| Epigenomic signatures underpin the axonal regenerative ability of dorsal root ganglia sensory neurons I Palmisano, MC Danzi, TH Hutson, L Zhou, E McLachlan, E Serger, ... Nature neuroscience 22 (11), 1913-1924, 2019 | 77 | 2019 |
| HiCNN: a very deep convolutional neural network to better enhance the resolution of Hi-C data T Liu, Z Wang Bioinformatics 35 (21), 4222-4228, 2019 | 61 | 2019 |
| TADKB: Family classification and a knowledge base of topologically associating domains T Liu, J Porter, C Zhao, H Zhu, N Wang, Z Sun, YY Mo, Z Wang BMC genomics 20, 1-17, 2019 | 38 | 2019 |
| Benchmarking deep networks for predicting residue-specific quality of individual protein models in CASP11 T Liu, Y Wang, J Eickholt, Z Wang Scientific reports 6 (1), 19301, 2016 | 37 | 2016 |
| SOV_refine: a further refined definition of segment overlap score and its significance for protein structure similarity T Liu, Z Wang Source code for biology and medicine 13, 1-10, 2018 | 20 | 2018 |
| HiCNN2: enhancing the resolution of Hi-C data using an ensemble of convolutional neural networks T Liu, Z Wang Genes 10 (11), 862, 2019 | 19 | 2019 |
| PANDA2: protein function prediction using graph neural networks C Zhao, T Liu, Z Wang NAR genomics and bioinformatics 4 (1), lqac004, 2022 | 18 | 2022 |
| The Polycomb protein RING1B enables estrogen-mediated gene expression by promoting enhancer–promoter interaction and R-loop formation Y Zhang, T Liu, F Yuan, L Garcia-Martinez, KD Lee, S Stransky, S Sidoli, ... Nucleic acids research 49 (17), 9768-9782, 2021 | 18 | 2021 |
| Reconstructing high-resolution chromosome three-dimensional structures by hi-C complex networks T Liu, Z Wang BMC bioinformatics 19, 39-50, 2018 | 17 | 2018 |
| scHiCNorm: a software package to eliminate systematic biases in single-cell Hi-C data T Liu, Z Wang Bioinformatics 34 (6), 1046-1047, 2018 | 17 | 2018 |
| Predicting protein residue-residue contacts using random forests and deep networks J Luttrell, T Liu, C Zhang, Z Wang BMC bioinformatics 20, 115-127, 2019 | 10 | 2019 |
| normGAM: an R package to remove systematic biases in genome architecture mapping data T Liu, Z Wang BMC genomics 20, 1-8, 2019 | 8 | 2019 |
| Measuring the three-dimensional structural properties of topologically associating domains T Liu, Z Wang 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2018 | 7 | 2018 |
| scHiCEmbed: bin-specific embeddings of single-cell Hi-C data using graph auto-encoders T Liu, Z Wang Genes 13 (6), 1048, 2022 | 6 | 2022 |
| Exploring the 2D and 3D structural properties of topologically associating domains T Liu, Z Wang BMC bioinformatics 20, 1-10, 2019 | 4 | 2019 |
| MASS: predict the global qualities of individual protein models using random forests and novel statistical potentials T Liu, Z Wang BMC bioinformatics 21 (Suppl 4), 246, 2020 | 3 | 2020 |
| 基于 OPM 的安全起源模型 刘通， 王凤英 计算机应用研究 30 (10), 3117-3120, 2013 | 3 | 2013 |
| 基于 Merkle 树的起源完整性解决方案 刘通， 王凤英 山东理工大学学报: 自然科学版 26 (3), 68-71, 2012 | 3 | 2012 |
| HiC4D: forecasting spatiotemporal Hi-C data with residual ConvLSTM T Liu, Z Wang Briefings in Bioinformatics 24 (5), bbad263, 2023 | 2 | 2023 |
Zheng WangAssociate Professor, Department of Computer Science, University of MiamiVerified email at miami.edu
