| Trends in the development of miRNA bioinformatics tools L Chen, L Heikkinen, C Wang, Y Yang, H Sun, G Wong Briefings in Bioinformatics 20 (5), 1836-1852, 2019 | 567 | 2019 |
| The bioinformatics toolbox for circRNA discovery and analysis L Chen, C Wang, H Sun, J Wang, Y Liang, Y Wang, G Wong Briefings in bioinformatics 22 (2), 1706-1728, 2021 | 271 | 2021 |
| Warburg effects in cancer and normal proliferating cells: two tales of the same name H Sun, L Chen, S Cao, Y Liang, Y Xu Genomics, proteomics & bioinformatics 17 (3), 273-286, 2019 | 69 | 2019 |
| Metabolic reprogramming in cancer is induced to increase proton production H Sun, Y Zhou, MF Skaro, Y Wu, Z Qu, F Mao, S Zhao, Y Xu Cancer Research 80 (5), 1143-1155, 2020 | 50 | 2020 |
| Fenton reactions drive nucleotide and ATP syntheses in cancer H Sun, C Zhang, S Cao, T Sheng, N Dong, Y Xu Journal of molecular cell biology 10 (5), 448-459, 2018 | 47 | 2018 |
| miRNA arm switching identifies novel tumour biomarkers L Chen, H Sun, C Wang, Y Yang, M Zhang, G Wong EBioMedicine 38, 37-46, 2018 | 44 | 2018 |
| Noninvasive application of mesenchymal stem cell spheres derived from hESC accelerates wound healing in a CXCL12-CXCR4 axis-dependent manner X Wang, B Jiang, H Sun, D Zheng, Z Zhang, L Yan, E Li, Y Wu, RH Xu Theranostics 9 (21), 6112, 2019 | 36 | 2019 |
| Intrathecal delivery of human ESC-derived mesenchymal stem cell spheres promotes recovery of a primate multiple sclerosis model L Yan, B Jiang, Y Niu, H Wang, E Li, Y Yan, H Sun, Y Duan, S Chang, ... Cell Death Discovery 4 (1), 89, 2018 | 32 | 2018 |
| Essential protein identification based on essential protein–protein interaction prediction by integrated edge weights Y Jiang, Y Wang, W Pang, L Chen, H Sun, Y Liang, E Blanzieri Methods 83, 51-62, 2015 | 25 | 2015 |
| Elucidation of Functional Roles of Sialic Acids in Cancer Migration H Sun, Y Zhou, H Jiang, Y Xu Frontiers in Oncology 10, 401, 2020 | 23 | 2020 |
| Identification of essential proteins based on ranking edge-weights in protein-protein interaction networks Y Wang, H Sun, W Du, E Blanzieri, G Viero, Y Xu, Y Liang PloS one 9 (9), e108716, 2014 | 22 | 2014 |
| Molecular Subtyping of Cancer based on Robust Graph Neural Network and Multi-omics Data Integration C Yin, Y Cao, P Sun, H Zhang, Z Li, Y Xu, H Sun Frontiers in Genetics, 934, 2022 | 18 | 2022 |
| Unsupervised nonlinear feature selection from high-dimensional signed networks Q Huang, T Xia, H Sun, M Yamada, Y Chang Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4182-4189, 2020 | 14 | 2020 |
| Molecular Subtyping of Cancer based on Distinguishing Co-expression Modules and Machine Learning P Sun, Y Wu, C Yin, H Jiang, Y XU, H Sun Frontiers in Genetics, 636, 2022 | 11 | 2022 |
| Gene regulatory network inference based on causal discovery integrating with graph neural network K Feng, H Jiang, C Yin, H Sun Quantitative Biology 11 (4), 434-450, 2023 | 7 | 2023 |
| Identification of Cancer Driver Genes by Integrating Multiomics Data with Graph Neural Networks H Song, C Yin, Z Li, K Feng, Y Cao, Y Gu, H Sun Metabolites 13 (3), 339, 2023 | 7 | 2023 |
| CaMeRe: A Novel Tool for Inference of Cancer Metabolic Reprogramming H Li, J Zhou, H Sun, Z Qiu, X Gao, Y Xu Frontiers in Oncology 10, 207, 2020 | 5 | 2020 |
| Identification of key somatic oncogenic mutation based on a confounder-free causal inference model Y Liu, J Sun, H Sun, Y Chang PLOS Computational Biology 18 (9), e1010529, 2022 | 4 | 2022 |
| Metabolic reprogramming in cancer: the bridge that connects intracellular stresses and cancer behaviors Y Zhou, H Sun, Y Xu National Science Review 7 (8), 1270-1273, 2020 | 4 | 2020 |
| De-confounding representation learning for counterfactual inference on continuous treatment via generative adversarial network Y Zhao, Q Huang, H Zeng, Y Peng, H Sun Data Mining and Knowledge Discovery, 1-22, 2024 | 3 | 2024 |
