| Genome-scale characterization of RNA tertiary structures and their functional impact by RNA solvent accessibility prediction Y Yang, X Li, H Zhao, J Zhan, J Wang, Y Zhou Rna 23 (1), 14-22, 2017 | 30 | 2017 |
| A novel single-cell based method for breast cancer prognosis X Li, L Liu, GJ Goodall, A Schreiber, T Xu, J Li, TD Le PLoS computational biology 16 (8), e1008133, 2020 | 27 | 2020 |
| Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data J Tanevski, T Nguyen, B Truong, N Karaiskos, ME Ahsen, X Zhang, C Shu, ... Life Science Alliance 3 (11), 2020 | 19 | 2020 |
| Mining stable patterns in multiple correlated databases Y Lin, X Hu, X Li, X Wu Decision support systems 56, 202-210, 2013 | 14 | 2013 |
| Identifying preeclampsia-associated genes using a control theory method X Li, L Liu, C Whitehead, J Li, B Thierry, TD Le, M Winter Briefings in Functional Genomics 21 (4), 296-309, 2022 | 7 | 2022 |
| Uncovering the roles of microRNAs/lncRNAs in characterising breast cancer subtypes and prognosis X Li, B Truong, T Xu, L Liu, J Li, TD Le BMC bioinformatics 22, 1-22, 2021 | 7 | 2021 |
| Dynamic cancer drivers: a causal approach for cancer driver discovery based on bio-pathological trajectories AM Cifuentes-Bernal, VVH Pham, X Li, L Liu, J Li, T Duy Le Briefings in Functional Genomics 21 (6), 455-465, 2022 | 6 | 2022 |
| A pseudotemporal causality approach to identifying miRNA–mRNA interactions during biological processes AM Cifuentes-Bernal, VV Pham, X Li, L Liu, J Li, TD Le Bioinformatics 37 (6), 807-814, 2021 | 6 | 2021 |
| Predicting cellular position in the Drosophila embryo from Single-Cell Transcriptomics data J Tanevski, T Nguyen, B Truong, N Karaiskos, ME Ahsen, X Zhang, C Shu, ... bioRxiv, 796029, 2019 | 6 | 2019 |
| Robust feature generation for protein subchloroplast location prediction with a weighted GO transfer model X Li, X Wu, G Wu Journal of theoretical biology 347, 84-94, 2014 | 6 | 2014 |
| PAN: Personalized annotation-based networks for the prediction of breast cancer relapse T Nguyen, SC Lee, TP Quinn, B Truong, X Li, T Tran, S Venkatesh, TD Le IEEE/ACM Transactions on Computational Biology and Bioinformatics 18 (6 …, 2021 | 5 | 2021 |
| miRspongeR 2.0: an enhanced R package for exploring miRNA sponge regulation J Zhang, L Liu, W Zhang, X Li, C Zhao, S Li, J Li, TD Le Bioinformatics Advances 2 (1), vbac063, 2022 | 3 | 2022 |
| The winning methods for predicting cellular position in the DREAM single-cell transcriptomics challenge VVH Pham, X Li, B Truong, T Nguyen, L Liu, J Li, TD Le Briefings in bioinformatics 22 (3), bbaa181, 2021 | 3 | 2021 |
| Personalized Annotation-based Networks (PAN) for the Prediction of Breast Cancer Relapse T Nguyen, SC Lee, TP Quinn, B Truong, X Li, T Tran, S Venkatesh, TD Le bioRxiv, 534628, 2019 | 2 | 2019 |
| On the α-universal multiple I restriction method for general fuzzy reasoning Y Tang, X Li 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 404-411, 2014 | 2 | 2014 |
| Stabilising Job Survival Analysis for Disability Employment Services in Unseen Environments HX Tran, TD Le, J Li, L Liu, X Li, J Liu, T Waters Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 1 | 2023 |
| Stable breast cancer prognosis X Li, L Liu, J Li, TD Le bioRxiv, 2021.09. 13.460002, 2021 | 1 | 2021 |
| Subchloroplast location prediction via homolog knowledge transfer and feature selection X Li, X Wu, G Wu, X Hu Proceedings of the AAAI Conference on Artificial Intelligence 27 (1), 1631-1632, 2013 | | 2013 |
