| Predicting drug response of tumors from integrated genomic profiles by deep neural networks YC Chiu, HIH Chen, T Zhang, S Zhang, A Gorthi, LJ Wang, Y Huang, ... BMC medical genomics 12, 143-155, 2019 | 222 | 2019 |
| Viral and cellular N6-methyladenosine and N6,2′-O-dimethyladenosine epitranscriptomes in the KSHV life cycle B Tan, H Liu, S Zhang, SR Da Silva, L Zhang, J Meng, X Cui, H Yuan, ... Nature microbiology 3 (1), 108-120, 2018 | 159 | 2018 |
| MeT-DB V2.0: elucidating context-specific functions of N6-methyl-adenosine methyltranscriptome H Liu, H Wang, Z Wei, S Zhang, G Hua, SW Zhang, L Zhang, SJ Gao, ... Nucleic acids research 46 (D1), D281-D287, 2018 | 116 | 2018 |
| Prediction of drug–target interaction by label propagation with mutual interaction information derived from heterogeneous network XY Yan, SW Zhang, SY Zhang Molecular BioSystems 12 (2), 520-531, 2016 | 64 | 2016 |
| FIONA1‐Mediated m6A Modification Regulates the Floral Transition in Arabidopsis T Xu, X Wu, CE Wong, S Fan, Y Zhang, S Zhang, Z Liang, H Yu, L Shen Advanced Science 9 (6), 2103628, 2022 | 59 | 2022 |
| Bioinformatics approaches for deciphering the epitranscriptome: recent progress and emerging topics L Liu, B Song, J Ma, Y Song, SY Zhang, Y Tang, X Wu, Z Wei, K Chen, ... Computational and structural biotechnology journal 18, 1587-1604, 2020 | 54 | 2020 |
| Prediction of lncRNA-disease associations by integrating diverse heterogeneous information sources with RWR algorithm and positive pointwise mutual information XN Fan, SW Zhang, SY Zhang, K Zhu, S Lu BMC bioinformatics 20, 1-12, 2019 | 52 | 2019 |
| GSAE: an autoencoder with embedded gene-set nodes for genomics functional characterization HIH Chen, YC Chiu, T Zhang, S Zhang, Y Huang, Y Chen BMC systems biology 12, 45-57, 2018 | 51 | 2018 |
| m6A-Driver: Identifying Context-Specific mRNA m6A Methylation-Driven Gene Interaction Networks SY Zhang, SW Zhang, L Liu, J Meng, Y Huang PLoS computational biology 12 (12), e1005287, 2016 | 44 | 2016 |
| Prediction and interpretation of cancer survival using graph convolution neural networks R Ramirez, YC Chiu, SY Zhang, J Ramirez, Y Chen, Y Huang, YF Jin Methods 192, 120-130, 2021 | 41 | 2021 |
| Global analysis of N6-methyladenosine functions and its disease association using deep learning and network-based methods SY Zhang, SW Zhang, XN Fan, J Meng, Y Chen, SJ Gao, Y Huang PLoS computational biology 15 (1), e1006663, 2019 | 38 | 2019 |
| m6A-express: uncovering complex and condition-specific m6A regulation of gene expression T Zhang, SW Zhang, SY Zhang, SJ Gao, Y Chen, Y Huang Nucleic acids research 49 (20), e116-e116, 2021 | 37 | 2021 |
| FunDMDeep-m6A: identification and prioritization of functional differential m6A methylation genes SY Zhang, SW Zhang, XN Fan, T Zhang, J Meng, Y Huang Bioinformatics 35 (14), i90-i98, 2019 | 33 | 2019 |
| DRUM: Inference of Disease-Associated m6A RNA Methylation Sites From a Multi-Layer Heterogeneous Network Y Tang, K Chen, X Wu, Z Wei, SY Zhang, B Song, SW Zhang, Y Huang, ... Frontiers in Genetics 10, 266, 2019 | 28 | 2019 |
| Prioritization of candidate disease genes by enlarging the seed set and fusing information of the network topology and gene expression SW Zhang, DD Shao, SY Zhang, YB Wang Molecular BioSystems 10 (6), 1400-1408, 2014 | 19 | 2014 |
| lncRNA_Mdeep: an alignment-free predictor for distinguishing long non-coding RNAs from protein-coding transcripts by multimodal deep learning XN Fan, SW Zhang, SY Zhang, JJ Ni International Journal of Molecular Sciences 21 (15), 5222, 2020 | 17 | 2020 |
| Recent advances in functional annotation and prediction of the epitranscriptome SY Zhang, SW Zhang, T Zhang, XN Fan, J Meng Computational and Structural Biotechnology Journal 19, 3015-3026, 2021 | 15 | 2021 |
| Shaping the landscape of N6-methyladenosine RNA methylation in Arabidopsis CE Wong, S Zhang, T Xu, Y Zhang, ZWN Teo, A Yan, L Shen, H Yu Plant Physiology 191 (3), 2045-2063, 2023 | 13 | 2023 |
| Single-nucleus sequencing deciphers developmental trajectories in rice pistils C Li, S Zhang, X Yan, P Cheng, H Yu Developmental Cell 58 (8), 694-708. e4, 2023 | 9 | 2023 |
| N6-methyladenosine-mediated feedback regulation of abscisic acid perception via phase-separated ECT8 condensates in Arabidopsis X Wu, T Su, S Zhang, Y Zhang, CE Wong, J Ma, Y Shao, C Hua, L Shen, ... Nature Plants 10 (3), 469-482, 2024 | 6 | 2024 |
