| GraphDTA: predicting drug–target binding affinity with graph neural networks T Nguyen, H Le, TP Quinn, T Nguyen, TD Le, S Venkatesh Bioinformatics 37 (8), 1140-1147, 2021 | 856 | 2021 |
| Assessment of network module identification across complex diseases S Choobdar, ME Ahsen, J Crawford, M Tomasoni, T Fang, D Lamparter, ... Nature methods 16 (9), 843-852, 2019 | 317 | 2019 |
| CancerSubtypes: an R/Bioconductor package for molecular cancer subtype identification, validation and visualization T Xu, TD Le, L Liu, N Su, R Wang, B Sun, A Colaprico, G Bontempi, J Li Bioinformatics 33 (19), 3131-3133, 2017 | 220 | 2017 |
| A fast PC algorithm for high dimensional causal discovery with multi-core PCs TD Le, T Hoang, J Li, L Liu, H Liu, S Hu IEEE/ACM transactions on computational biology and bioinformatics 16 (5 …, 2016 | 201 | 2016 |
| Multi-source causal feature selection K Yu, L Liu, J Li, W Ding, TD Le IEEE transactions on pattern analysis and machine intelligence 42 (9), 2240-2256, 2019 | 117 | 2019 |
| Computational methods for identifying miRNA sponge interactions TD Le, J Zhang, L Liu, J Li Briefings in bioinformatics 18 (4), 577-590, 2017 | 107 | 2017 |
| Inferring microRNA–mRNA causal regulatory relationships from expression data TD Le, L Liu, A Tsykin, GJ Goodall, B Liu, BY Sun, J Li Bioinformatics 29 (6), 765-771, 2013 | 102 | 2013 |
| Identifying cancer subtypes from miRNA-TF-mRNA regulatory networks and expression data T Xu, TD Le, L Liu, R Wang, B Sun, J Li PloS one 11 (4), e0152792, 2016 | 88 | 2016 |
| Causal decision trees J Li, S Ma, T Le, L Liu, J Liu IEEE Transactions on Knowledge and Data Engineering 29 (2), 257-271, 2016 | 86 | 2016 |
| Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth AL Tarca, BA Pataki, R Romero, M Sirota, Y Guan, R Kutum, ... Cell Reports Medicine 2 (6), 2021 | 80 | 2021 |
| Mining causal association rules J Li, TD Le, L Liu, J Liu, Z Jin, B Sun 2013 IEEE 13th International Conference on Data Mining Workshops, 114-123, 2013 | 79 | 2013 |
| miRBaseConverter: an R/Bioconductor package for converting and retrieving miRNA name, accession, sequence and family information in different versions of miRBase T Xu, N Su, L Liu, J Zhang, H Wang, W Zhang, J Gui, K Yu, J Li, TD Le BMC bioinformatics 19 (19), 514, 2018 | 76 | 2018 |
| LncmiRSRN: identification and analysis of long non-coding RNA related miRNA sponge regulatory network in human cancer J Zhang, L Liu, J Li, TD Le Bioinformatics 34 (24), 4232-4240, 2018 | 73 | 2018 |
| From observational studies to causal rule mining J Li, TD Le, L Liu, J Liu, Z Jin, B Sun, S Ma ACM Transactions on Intelligent Systems and Technology (TIST) 7 (2), 1-27, 2015 | 70 | 2015 |
| How do the existing fairness metrics and unfairness mitigation algorithms contribute to ethical learning analytics? OB Deho, C Zhan, J Li, J Liu, L Liu, T Duy Le British Journal of Educational Technology 53 (4), 822-843, 2022 | 67 | 2022 |
| Mining heterogeneous causal effects for personalized cancer treatment W Zhang, T Duy Le, L Liu, ZH Zhou, J Li Bioinformatics, 2017 | 59 | 2017 |
| From miRNA regulation to miRNA–TF co-regulation: computational approaches and challenges TD Le, L Liu, J Zhang, B Liu, J Li Briefings in bioinformatics 16 (3), 475-496, 2015 | 59 | 2015 |
| Practical approaches to causal relationship exploration J Li, L Liu, TD Le Springer, 2015 | 54* | 2015 |
| Inferring and analyzing module-specific lncRNA–mRNA causal regulatory networks in human cancer J Zhang, TD Le, L Liu, J Li Briefings in bioinformatics 20 (4), 1403-1419, 2019 | 50 | 2019 |
| Inferring microRNA and transcription factor regulatory networks in heterogeneous data TD Le, L Liu, B Liu, A Tsykin, GJ Goodall, K Satou, J Li BMC bioinformatics 14, 1-13, 2013 | 48 | 2013 |
Jiuyong Li (李久永)Professor of Computer Science, University of South AustraliaEmail verificata su unisa.edu.au
