Associate Professor Thuc Le

ARC Discovery Early Career Researcher UniSA STEM

Mawson Lakes Campus (D3-14)
tel +61 8 830 23996

email Thuc.Le@unisa.edu.au

Alternative contact

Available for media comment
Research Degree Supervisor

About me

Data mining
Cancer research
Machine learning
Causality
Bioinformatics

I am looking for a PhD student working on Causal Inference, PhD scholarship

My publications: Google Scholar and go here to download the papers.

I am currently a DECRA Fellow (2020-2022), and before that, an NHMRC ECR Fellow in Bioinformatics/Computational Biology (2017-2019). Bioinformatics is an inter-disciplinary research area which uses knowledge in Computer Science, Mathematics, and Statistics to solve biological problems. My research focuses on the development of causal inference methods and their applications in Bioinformatics, particularly in gene regulatory networks, cancer drivers, non-coding RNAs, and cancer subtype discovery.

I have a diverse educational background with BSc and MSc in... Read more

UniSA STEM

Harnessing connections across science, technology, engineering and mathematics, UniSA STEM creates innovative solutions and groundbreaking developments across teaching, learning and research.

Tweets by @UniversitySA

About me

In the media

Date	Title
19/05/2015	The Lead South Australia, http://www.theleadsouthaustralia.com.au/industries/health/bioinformatics-points-the-way-to-cancers-genetic-causes/

Research

Research focus

Information and Computing Sciences
Biological Sciences
Artificial Intelligence and Image Processing
Biochemistry and Cell Biology
Data Format

Highlights

My research focuses on the development of causal inference methods and their applications in Bioinformatics, particularly in gene regulatory networks, cancer drivers, non-coding RNAs, and cancer subtype discovery.

Research

Outputs

Research outputs for the last seven years are shown below. To see earlier years visit ORCID, ResearcherID or Scopus

Open access indicates that an output is open access.

Books

Year	Output
2015	Li, J, Liu, L & Le, TD 2015, Practical approaches to causal relationship exploration, Springer, US.

Chapters

Year	Output
2022	Tran, HX, Le, TD, Li, J, Liu, L, Liu, J, Zhao, Y & Waters, T 2022, 'Recommending personalized interventions to increase employability of disabled jobseekers', in J Gama et al. (eds), Advances in Knowledge Discovery and Data Mining: 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16–19, 2022, Proceedings, Part III, Springer, Switzerland, pp. 92-104. 1
2020	Zhang, J, Nguyen, T, Truong, B, Liu, L, Li, J & Le, TD 2020, 'Computational methods for predicting autism spectrum disorder from gene expression data', ADMA 2020: Advanced Data Mining and Applications, Springer, Singapore, pp. 395-409.
2019	Le, TD, Ong, KL, Wong, S, Zhao, Y, Jin, WH, Liu, L & Williams, G 2019, 'Preface', Data mining: AusDM: Australasian Conference on Data Mining, Springer Nature, Singapore, pp. v-vi.

Journal Articles

Year	Output
2022	Cheng, D, Li, J, Liu, L, Le, TD, Liu, J & Yu, K 2022, 'Sufficient dimension reduction for average causal effect estimation', Data Mining and Knowledge Discovery, vol. 36, no. 3, pp. 1174-1196. Open access
2022	Cheng, D, Li, J, Liu, L, Liu, J & Le, TD 2022, 'Data-driven causal effect estimation based on graphical causal modelling: a survey', Journal of the Association for Computing Machinery (ACM), online, pp. 1-25. Open access
2022	Cheng, D, Li, J, Liu, L, Yu, K, Le, TD & Liu, J 2022, 'Toward unique and unbiased causal effect estimation from data with hidden variables', IEEE Transactions on Neural Networks and Learning Systems, online, pp. 1-13. 2 1 1
2022	Cheng, D, Li, J, Liu, L, Zhang, J, Liu , J & Le, TD 2022, 'Local search for efficient causal effect estimation', IEEE Transactions on Knowledge and Data Engineering, online, pp. 1-14. Open access
2022	Cifuentes Bernal, AM, Pham, VVH, Li, X, Liu, L, Li, J & Le, TD 2022, 'Dynamic cancer drivers: a causal approach for cancer driver discovery based on bio-pathological trajectories', Briefings in Functional Genomics, vol. 21, no. 6, pp. 455-465. Open access
2022	Deho, OB, Zhan, C, Li, J, Liu, J, Liu, L & Le, TD 2022, 'How do the existing fairness metrics and unfairness mitigation algorithms contribute to ethical learning analytics?', British Journal of Educational Technology, vol. 53, no. 4, pp. 822-843. Open access 6 3 3
2022	Li, J, Liu, L, Zhang, S, Ma, S, Le, TD & Liu, J 2022, 'Causal heterogeneity discovery by bottom-up pattern search for personalised decision making', Applied Intelligence, online, pp. 1-15. Open access 3
2022	Li, X, Liu, L, Whitehead, C, Li, J, Thierry, B, Le, TD & Winter, M 2022, 'Identifying preeclampsia-associated genes using a control theory method', Briefings in Functional Genomics, vol. 21, no. 4, pp. 296-309. Open access 1
2022	Zhang, J, Liu, L, Xu, T, Zhang, W, Li, J, Rao, N & Le, TD 2022, 'Time to infer miRNA sponge modules', Wiley interdisciplinary reviews. RNA, vol. 13, no. 2, pp. 1-21. Open access 5 6 2
2022	Zhang, J, Liu, L, Zhang, W, Li, X, Zhao, C, Li, S, Li, J & Le, TD 2022, 'miRspongeR 2.0: an enhanced R package for exploring miRNA sponge regulation', Bioinformatics Advances, vol. 2, no. 1, article no. vbac063, pp. 1-3. Open access
2021	Chaudhary, MS, Pham, VVH & Le, TD 2021, 'NIBNA: a network-based node importance approach for identifying breast cancer drivers', Bioinformatics, vol. 37, no. 17, pp. 2521-2528. Open access 3 2 4
2021	Li, J, Zhang, W, Liu, L, Yu, K, Le, TD & Liu, J 2021, 'A general framework for causal classification', International Journal of Data Science and Analytics, vol. 11, no. 2, pp. 127-139. 3 4
2021	Li, X, Truong, B, Xu, T, Liu, L, Li, J & Le, TD 2021, 'Uncovering the roles of microRNAs/lncRNAs in characterising breast cancer subtypes and prognosis', BMC Bioinformatics, vol. 300, pp. 1-22. Open access 2 2 2
2021	Nguyen, T, Le, H, Quinn, TP, Nguyen, T, Le, TD & Venkatesh, S 2021, 'GraphDTA: predicting drug-target binding affinity with graph neural networks', Bioinformatics, vol. 37, no. 8, pp. 1140-1147. 134 127 1
2021	Nguyen, T, Lee, SC, Quinn, TP, Truong, B, Li, X, Tran, T, Venkatesh, S & Le, TD 2021, 'PAN: Personalized Annotation-Based networks for the prediction of Breast Cancer relapse', IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 18, no. 6, pp. 2841 - 2847. 3 4 1
2021	Pham, VV, Li, X, Truong, B, Nguyen, T, Liu, L, Li, J & Le, TD 2021, 'The winning methods for predicting cellular position in the DREAM single-cell transcriptomics challenge', Briefings in Bioinformatics, vol. 22, no. 3, pp. 1-4. Open access 2 10
2021	Pham, VV, Liu, L, Bracken, CP, Nguyen, T, Goodall, GJ, Li, J & Le, TD 2021, 'pDriver: a novel method for unravelling personalized coding and miRNA cancer drivers', Bioinformatics, vol. 37, no. 9, pp. 3285-3292. Open access 1 1 2
2021	Pham, VVH, Liu, L, Bracken, C, Goodall, G, Li, J & Le, TD 2021, 'Computational methods for cancer driver discovery: a survey', Theranostics, vol. 11, no. 11, pp. 5553-5568. Open access 8 8 1
2021	Zhang, J, Liu, L, Xu, T, Zhang, W, Zhao, C, Li, S, Li, J, Rao, N & Le, TD 2021, 'Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data', BMC Bioinformatics, vol.22, no. 1, article no. 578, pp. 1-19. Open access 2 2 10
2021	Zhang, J, Liu, L, Xu, T, Zhang, W, Zhao, C, Li, S, Li, J, Rao, N & Le, TD 2021, 'miRSM: an R package to infer and analyse miRNA sponge modules in heterogeneous data', RNA Biology, vol. 18, no. 12, pp. 2308-2320. Open access 3 1 1
2020	Cifuentes-Bernal, AM, Pham, VV, Li, X, Liu, L, Li, J & Le, TD 2020, 'A pseudotemporal causality approach to identifying miRNA-mRNA interactions during biological processes', Bioinformatics, vol. 37, no. 6, pp. 807-814. Open access 2 2 9
2020	Li, J, Liu, L, Le, TD & Liu, J 2020, 'Accurate data-driven prediction does not mean high reproducibility', Nature Machine Intelligence, vol. 2, pp. 13-15. 21 18 80
2020	Li, X, Liu, L, Goodall, GJ, Schreiber, A, Xu, T, Li, J & Le, TD 2020, 'A novel single-cell based method for breast cancer prognosis', PLoS Computational Biology, vol. 16, no. 8, article no. e1008133, pp. 1-20. Open access 6 7 11
2020	Pan, J, Cui, T, Le, TD, Li, X & Zhang, J 2020, 'Multi-group transfer learning on multiple latent spaces for text classification', IEEE Access, vol. 8, article no. 9051683, pp. 64120-64130. Open access 3 2
2020	Pham, VV, Liu, L, Bracken, CP, Goodall, GJ, Li, J & Le, TD 2020, 'DriverGroup: a novel method for identifying driver gene groups', Bioinformatics, vol. 36, no. S2, pp. i583-i591. Open access 2 3 1
2020	Tanevski, J, Nguyen, T, Truong, B, Karaiskos, N, Pham, HV, Xiaomei, L, Le, TD & Meyer, P and 30 other authors & 1 consortia 2020, 'Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data', Life Science Alliance, vol. 3, no. 11, article no. e202000867, pp. 1-13. Open access 10 7 13
2020	Truong, B, Zhou, X, Shin, J, Li, J, van der Werf, JH, Le, TD & Lee, SH 2020, 'Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives', Nature Communications, vol. 11, article no. 3074, pp. 1-11. Open access 17 13 32
2020	Yu, K, Liu, L, Li, J, Ding, W & Le, TD 2020, 'Multi-source causal feature selection', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 9, pp.2240-2256. Open access 46 41
2020	Zhang, J, Xu, T, Liu, L, Zhang, W, Zhao, C, Li, S, Li, J, Rao, N & Le, TD 2020, 'LMSM: A modular approach for identifying lncRNA related miRNA sponge modules in breast cancer', PLoS Computational Biology, vol. 16, no. 4, article no. e1007851. Open access 13 12 3
2019	Brown, P, Zhou, Y, Li, J, Lim, R, You, Y, Li, Y, Le, TD & Cao, Z 2 explicit authors and 1 consortia; internal authors (nos.3, 4, 5, 6, 7) are listed as part of the RELISH Consortium 2019, 'Large expert-curated database for benchmarking document similarity detection in biomedical literature search', Database : The Journal of Biological Databases and Curation, article no. baz085, pp. 1-66. Open access 13 12 27
2019	Choobdar, S, Ahsen, ME, Crawford, J, Tomasoni, M, Le, TD, Li, J, Liu, L, Zhang, W & Marbach, D and 168 other authors and 1 consortia 2019, 'Assessment of network module identification across complex diseases', Nature Methods, vol. 16, no. 9, pp. 843-852. Open access 107 105 107
2019	Le, TD, Hoang, T, Li, J, Liu, L, Liu, H & Hu, S 2019, 'A fast PC algorithm for high dimensional causal discovery with multi-core PCs', IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 13, no. 9, pp. 1483-1495. Open access 37 32 4
2019	MA, S, Liu, L, LI, J & LE, TD 2019, 'Data-driven discovery of causal interactions', International Journal of Data Science and Analytics, vol. 8, pp. 285-297. Open access 1 1
2019	Ma, S, Li, J, Liu, L & Le, TD 2019, 'Discovering context specific causal relationships', Intelligent Data Analysis, vol. 23, no. 4, pp. 917-931. Open access
2019	Pham, VV, Liu, L, Bracken, CP, Goodall, GJ, Long, Q, Li, J & Le, TD 2019, 'CBNA: A control theory based method for identifying coding and non-coding cancer drivers', PLoS Computational Biology, vol. 15, no. 12, article no. e1007538, pp. 1-12. Open access 13 14 5
2019	Pham, VV, Zhang, J, Liu, L, Truong, B, Xu, T, Nguyen, TT, Li, J & Le, TD 2019, 'Identifying miRNA-mRNA regulatory relationships in breast cancer with invariant causal prediction', BMC Bioinformatics, vol. 20, no. 1, article no. 143, pp. 1-12. Open access 14 16 5
2019	Pillman, KA, Scheer, KG, Hackett-Jones, E, Saunders, K, Bert, AG, Toubia, J, Whitfield, HJ, Sapkota, S, Sourdin, L, Pham, H, Le, TD, Cursons, J, Davis, MJ, Gregory, PA, Goodall, GJ & Bracken, CP 2019, 'Extensive transcriptional responses are co-ordinated by microRNAs as revealed by Exon-Intron Split Analysis (EISA)', Nucleic Acids Research, vol. 47, no. 16, pp. 8606-8619. Open access 5 4 4
2019	Zhang, J, Le, TD, Liu, L & Li, J 2019, 'Inferring and analyzing module-specific lncRNA-mRNA causal regulatory networks in human cancer', Briefings in Bioinformatics, vol. 20, no. 4, pp. 1403-1419. Open access 27 27 1
2019	Zhang, J, Liu, L, Xu, T, Xie, Y, Zhao, C, Li, J & Le, TD 2019, 'MiRspongeR: An R/Bioconductor package for the identification and analysis of miRNA sponge interaction networks and modules', BMC Bioinformatics, vol. 20, no. 1, article no. 235, pp. 1-12. Open access 27 23 4
2019	Zhang, J, Pham, VVH, Liu, L, Xu, T, Truong, B, Li, J, Rao, N & Le, TD 2019, 'Identifying miRNA synergism using multiple-intervention causal inference', BMC Bioinformatics, vol. 20, article no. 613, pp. 1-11. Open access 9 10
2018	Thuyen, T, Suriyanarayanan, T, Zeng, G, Le, TD, Liu, L, Li, J, Tong, C, Wang, Y & Seneviratne, CJ 2018, 'Use of haploid model of Candida albicans to uncover mechanism of action of a novel antifungal agent', Frontiers in Cellular and Infection Microbiology, vol. 8, article no. 164, pp. 1-14. Open access 11 11 1
2018	Xu, T, Su, N, Liu, L, Zhang, J, Wang, H, Zhang, W, Gui, J, Yu, K, Li, J & Le, T 2018, 'miRBaseConverter: an R/Bioconductor package for converting and retrieving miRNA name, accession, sequence and family information in different versions of miRBase', BMC Bioinformatics, vol. 19, article no. 514, pp. 1-10. Open access 39 37 1
2018	Zhang, J, Liu, L, Li, J & Le, TD 2018, 'LncmiRSRN: identification and analysis of long non-coding RNA related miRNA sponge regulatory network in human cancer', Bioinformatics, vol. 34, no. 24, pp. 4232-4240. 52 46 3
2018	Zhang, W, Le, DT, Lui, L & Li, J 2018, 'Estimating heterogeneous treatment effect by balancing heterogeneity and fitness', BMC Bioinformatics, vol. 19, article no. 518, pp. 1-12. Open access 3 2 1
2017	Le, TD, Zhang, J, Liu, L & Li, J 2017, 'Computational methods for identifying miRNA sponge interactions', Briefings in Bioinformatics, vol. 18, no. 4, pp. 577-590. Open access 67 58 2
2017	Li, J, Ma, S, Le, T, Liu, L & Liu, J 2017, 'Causal Decision Trees', IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 2, pp. 257-271. Open access 34 20 1
2017	Liu, H, Liu, L, Le, TD, Lee, I, Sun, S & Li, J 2017, 'Nonparametric sparse matrix decomposition for cross-view dimensionality reduction', IEEE Transactions on Multimedia, vol. 19, no. 8, article no. 7879190, pp. 1848-1859. 15 15
2017	Weijia Zhang , Le, TD, Liu, L, Zhou, Z-H & Li, J 2017, 'Mining heterogeneous causal effects for personalized cancer treatment', Bioinformatics, vol. 33, no. 15, pp. 2372-2378. Open access 19 18 5
2017	Xu, T, Le, TD, Liu, L, Su, N, Wang, R, Sun, B, Colaprico, A, Bontempi, G & Li, J 2017, 'CancerSubtypes: an R/Bioconductor package for molecular cancer subtype identification, validation and visualization', Bioinformatics, vol. 33, n. 19, pp. 3131-3133. Open access 125 120 17
2017	Zhang, J, Le, TD, Liu, L & Li, J 2017, 'Identifying miRNA sponge modules using biclustering and regulatory scores', BMC Bioinformatics, vol. 18, suppl. 3, article no. 44, pp. 1-12. Open access 16 14 2
2017	Zhang, J, Le, TD, Liu, L & Li, J 2017, 'Inferring miRNA sponge co-regulation of protein-protein interactions in human breast cancer', BMC Bioinformatics, vol. 18, no. 243, pp. 1-12. Open access 22 19 2
2016	Li, J, Le, TD, Liu, L, Liu, J, Jin, Z, Sun, B & Ma, S 2016, 'From observational studies to causal rule mining', ACM Transactions on Intelligent Systems and Technology, vol. 7, no. 2, article no. 14. Open access 30 12 1
2016	Ma, S, Li, J, Liu, L & Le, TD 2016, 'Mining combined causes in large data sets', Knowledge-Based Systems, vol. 92, pp. 104-111. Open access 15 10
2016	Masud, K, Liu, L, Le, TD & Li, J 2016, 'Identification of miRNA-mRNA regulatory modules by exploring collective group relationships', BMC Genomics, vol. 17, no. S1, pp. 71-84. Open access 23 18 2
2016	Weijia Zhang , Le, TD, Liu, L, Zhou, Z-H & Li, J 2016, 'Predicting miRNA targets by integrating gene regulatory knowledge with expression profiles', PLoS One, vol. 11, no. 4, article no. e0152860, pp. 1-19. Open access 14 16 2
2016	Xu, T, Le, TD, Liu, L, Wang, R, Sun, B & Li, J 2016, 'Identifying cancer subtypes from miRNA-TFmRNA regulatory networks and expression data', PLoS One, vol. 11, no. 4, pp. 1-20. Open access 57 41 8
2016	Zhang, J, Le, TD, Liu, L, He, J & Li Jiuyong, 2016, 'A novel framework for inferring condition-specific TF and miRNA co-regulation of protein-protein interactions', Gene, vol. 557, no. 1, pp. 55-64. 9 10 1
2016	Zhang, J, Le, TD, Liu, L, He, J & Li, J 2016, 'Identifying miRNA synergistic regulatory networks in heterogeneous human data via network motifs', Molecular Biosystems, vol. 12, no. 2, pp. 454-463. 8 8 1
2015	Le, TD, Liu, L, Zhang, J, Liu, B & Li, J 2015, 'From miRNA regulation to miRNA-TF co-regulation: computational approached and challenges', Briefings in Bioinformatics, vol. 16, no. 9, pp. 475-496. Open access 29 25 2
2015	Le, TD, Zhang, J, Liu, L & Li, J 2015, 'Ensemble methods for MiRNA target prediction from expression data', PLoS One, vol. 10, no. 6, pp. 1-19. Open access 26 19 2
2015	Le, TD, Zhang, J, Liu, L, Liu, H & Li, J 2015, 'miRLAB: An R Based Dry Lab for Exploring miRNA-mRNA Regulatory Relationships', PLoS One, vol. 10, no. 12, pp.1-15. Open access 24 18 8
2014	Zhang, J, Le, TD, Liu, L, Liu, B, He, J, Goodall, GJ & Li, J 2014, 'Inferring condition-specific miRNA activity from matched miRNA and mRNA expression data', Bioinformatics, v 30, no. 21, pp. 3070-3077. Open access 17 15 3
2014	Zhang, J, Le, TD, Liu, L, Liu, B, Jianfeng, H, Goodall, GJ & Li, J 2014, 'Identifying direct miRNA-mRNA causal regulatory relationships in heterogeneous data', Journal of Biomedical Informatics, vol. 52, pp. 438-447. Open access 23 22
2013	Le, TD, Liu, L, Liu, B, Tsykin, A, Goodall, G, Satou, K & Li, J 2013, 'Inferring microRNA and transcription factor regulatory networks in heterogeneous data', BMC Bioinformatics, vol. 14, article no. 92, pp. 1-13. Open access 37 38 4
2013	Le, TD, Liu, L, Tsykin, A, Goodall, GJ, Liu, B, Sun, B-Y & Li, J 2013, 'Inferring microRNA-mRNA causal regulatory relationships from expression data', Bioinformatics, vol. 29, no. 6, pp. 765-771. Open access 65 62 4

Conferences

Year	Output
2022	Cheng, D, Li, J, Liu, L, Zhang, J, Le, TD & Liu, J 2022, 'Ancestral instrument method for causal inference without complete knowledge', in Luc De Raedt (ed.), Thirty-First International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, pp. 4843-4849. Open access
2022	Le, TD, Liu, L, Kiciman, E, Triantafyllou, S & Liu, H 2022, 'The KDD 2022 workshop on causal discovery (CD2022)', Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Association for Computing Machinery, article no. 181896, pp. 4884-4885.
2022	Tran, HX, Le, TD, Li, J, Liu, L, Liu, J, Zhao, Y & Waters, T 2022, 'What is the most effective intervention to increase job retention for this disabled worker?', the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, ACM - Association for Computing Machinery Inc, pp. 3981-3991. Open access 1
2022	Xuan Tran, H, Le, TD, Zhao, Y & Waters, T 2022, 'Decision support for disability employment using counterfactual survival analysis', IEEE International Conference on Big Data, Big Data 2022, IEEE, pp. 2103-2112. Open access
2021	Lu, S, Liu, L, Li, J, Le, TD & Liu, J 2021, 'Divide and conquer: targeted adversary detection using proximity and dependency', in Z Gong, X Li, SG Oguducu, L Chen, BF Manjon, X Wu (eds), 12th IEEE International Conference on Big Knowledge, IEEE, pp. 125-132.
2021	Tran, HX, Le, TD, Li, J, Liu, L, Liu, J, Zhao, Y & Waters, T 2021, 'Intervention recommendation for improving disability employment', 8th IEEE International Conference on Big Data, Big Data 2020, IEEE, pp. 1671-1680. Open access 3 2
2021	Tran, HX, Le, TD, Li, J, Liu, L, Liu, J, Zhao, Y & Waters, T 2021, 'Recommending the most effective intervention to improve employment for job seekers with disability', The 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD'21), Association for Computing Machinery, pp. 3616-3626. Open access 3 1 31
2020	Cheng, D, Li, J, Liu, L, Liu, J, Yu, K & Le, TD 2020, 'Causal query in observational data with hidden variables', in G De Giacomo et al. (eds), 24th European Conference on Artificial Intelligence, ECAI 2020, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020, IOS Press, pp. 2551-2558. Open access 1
2020	Liu, J, Li, J, Ye, F, Liu, L, Le, T, Xiong, P & Liu, H-c 2020, 'Building fair predictive models', in M Gallagher, N Moustafa & E Lakshika (eds), 33rd Australasian Joint Conference on Artificial Intelligence, AI 2020, Springer Nature, pp. 216-229. Open access
2020	Lu, S, Liu, L, Li, J, Le, TD & Liu, J 2020, 'LoPAD: A local prediction approach to anomaly detection', 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, Springer, vol. 12085, pp. 660-673.
2020	Nguyen, T, Le, TD, Nguyen, DT & Venkatesh, S 2020, 'MrPC: causal structure learning in distributed systems', in H Yang et al. (eds.), ICONIP 2020 International Conference on Neural Information Processing, Springer, vol. 1332, pp. 87-94.
2019	Lu, S, Liu, L, Li, J & Le, TD 2019, 'Effective outlier detection based on Bayesian Network and Proximity', International Conference on Big Data, Big Data 2018, IEEE, article no. 8622230, pp. 134-139. Open access 2 1
2018	Le, TD, Xu, T, Liu, L, Shu, H, Hoang, T & Li, J 2018, 'ParallelPC: An R package for efficient causal exploration in genomic data', 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2018, Springer Nature, pp. 207-218. 6
2017	Le, TD, Zhang, J, Liu, L, Thanh Truong, BM, Hu, S, Xu, T & Li, J 2017, 'Identifying microRNA targets in epithelial-mesenchymal transition using joint-intervention causal inference', 8th International Conference on Computational Systems-Biology and Bioinformatics, (CSBio 2017), ACM - Association for Computing Machinery, pp. 34-41. 2
2017	Li, J, Liu, J, Liu, L, Thuc, DL, Ma, S & Han, Y 2017, 'Discrimination detection by causal effect estimation', IEEE International Conference on Big Data (IEEE Big Data), IEEE, pp. 1087-1094. Open access 7 5
2013	Li, J, Le, TD, Liu, L, Liu, J, Jin, Z & Sun, B 2013, 'Mining causal association rules', IEEE 13th International Conference on Data Mining Workshops 2013, IEEE Press, pp. 114-123. 34 26 2
2012	Jin, Z, Li, J, Liu, L, Le, TD, Sun, B & Wang, R 2012, 'Discovery of causal rules using partial association', 2012 IEEE 12th International Conference on Data Mining, IEEE, pp. 309-318. 25 19

Reports

Year	Output
2017	Le, TD 2017, Causal inference methods and applications in Bioinformatics: A Summary, Australia. Open access

External engagement & recognition

Collaborations

Highlights

Associate Editor:

Plos One
BMC Cancer

Conference/workshop Organiser of:

Causality Workshop 2018, 2019, 2020
BioinfoSummer 2016

Program committee chair/member of:

PC co-chair of Australasian Data Mining Conference 2019
AAAI, ICDM, PAKDD, InCOB, GIW

Paper reviewer for:

Bioinformatics
Plos Computational Biology
Nucleic Acids Research
BMC Bioinformatics
IEEE Transactions on Knowledge and Data Engineering (TKDE)
ACM Transactions on Intelligent Systems and Technology (ACM TIST)
Annals of Medicine Computers in Biology and Medicine
Plos One
Briefings in Bioinformatics

Grant reviewer for:

ARC
NHMRC

External engagement & recognition

Collaborations

Organisation	Country
Agency for Science Technology & Research (ASTAR)	UNITED STATES
Arizona State University	UNITED STATES
Children's Cancer Institute Australia	AUSTRALIA
Chinese Academy of Sciences	CHINA
Consilium Technology	AUSTRALIA
Consilium Technology Pty Ltd	AUSTRALIA
CSIRO Australia (Commonwealth Scientific Industrial Research Organisation)	AUSTRALIA
CSIRO Data61	AUSTRALIA
Dali University	CHINA
Deakin University	AUSTRALIA
East China Normal University	CHINA
Griffith University	AUSTRALIA
Heidelberg University	GERMANY
Heifei University of Technology	CHINA
Hong Kong Baptist University	HONG KONG
Icahn School of Medicine at Mount Sinai	UNITED STATES
Infinia ML	UNITED STATES
Institute of Medical and Veterinary Science	AUSTRALIA
Jiangsu Normal University	CHINA
Jiangsu University of Technology	CHINA
Kanazawa University	JAPAN
Kunming University of Science and Technology	CHINA
La Trobe University	AUSTRALIA
Max Delbrück Center for Molecular Medicine in the Helmholtz Association	GERMANY
Maxima Training Group (Aust) Ltd.	AUSTRALIA
Microsoft	AUSTRALIA
Microsoft Research	UNITED KINGDOM
Nanjing University	CHINA
Nanjing University of Science and Technology	CHINA
National University of Singapore	SINGAPORE
Nha Trang University	VIET NAM
Pham Ngoc Thach University of Medicine	VIET NAM
SA Pathology	AUSTRALIA
TJ Watson Research Center	UNITED STATES
Tufts University	UNITED STATES
University Libre Bruxelles	BELGIUM
University of Adelaide	AUSTRALIA
University of British Columbia	CANADA
University of Crete	GREECE
University of Electronic Science and Technology of China	CHINA
University of Lausanne	SWITZERLAND
University of Massachusetts Boston	UNITED STATES
University of Melbourne	AUSTRALIA
University of Michigan	UNITED STATES
University of New England	AUSTRALIA
University of Pennsylvania	UNITED STATES
University of Science and Technology of China	CHINA
University of South Australia	AUSTRALIA
University of Tasmania	AUSTRALIA
Walter and Eliza Hall Institute of Medical Research	AUSTRALIA
Zhejiang Normal University	CHINA

External engagement & recognition

Engagement/recognition	Year
Academic Editor PLOS One	2020
ARC Grant Reviewer Australian Research Council Discovery	2020
Associate Editor BMC Cancer Journal	2020
Discovery Early Career Researcher Award Australian Research Council Discovery	2020
HDR Thesis Examiner University of Sydney	2020
HDR Thesis Examiner Deakin University	2020
Academic Editor PLOS One	2019
PC Co-chair of Australasian Data Mining Conference Australian Computer Society (ACS)	2019
Visiting Professor University of Pennsylvania	2019
Conference and Workshop Organiser ACM SIGKDD Workshop on Causal Discovery	2018
Early Career Fellowship National Health and Medical Research Council (NHMRC)	2018
Member Australian Bioinformatics Network	2018
Member The Australian Bioinformatics And Computational Biology Society (ABACBS)	2018
Member Association for Computing Machinery (ACM) SIG-Bioinformatics	2018
Professional Member Association for Computing Machinery (ACM)	2018
Professional Member Institute of Electrical and Electronics Engineers (IEEE)	2018
Early Career Fellowship National Health and Medical Research Council (NHMRC)	2017
Member Australian Bioinformatics Network	2017
Member The Australian Bioinformatics And Computational Biology Society (ABACBS)	2017
Member Association for Computing Machinery (ACM) SIG-Bioinformatics	2017
Professional Member Association for Computing Machinery (ACM)	2017
Professional Member Institute of Electrical and Electronics Engineers (IEEE)	2017
Program Committee Member International Conference on Bioinformatics InCOB	2017
Board Member BioInfoSummer, University of Adelaide	2016
Conference and Workshop Organiser BioinfoSummer	2016
Contributor Movember Foundation	2016
Early Career Fellowship National Health and Medical Research Council (NHMRC)	2016
HDR Thesis Examiner Deakin University	2016
Program Committee Member, Causality Workshop 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016)	2016
Runner-up prize for DREAM challenge DREAM	2016
Cancer Research Fund Raising Campaign Movember Foundation	2015
Interviewed by The LEAD South Australia about bioinformatics research and the success in PhD research thesis The LEAD South Australia	2015
Invited by the SA Governor as an SA emerging scientist to talk to the HRH The Duke of Kent during his visit to Australia Government of South Australia	2015

Teaching & student supervision

Research degree supervision

Supervisions from 2010 shown

Thesis title	Student status
Causal inference methods for identification of subtypes of cancer based on multi-levelled biological data	Current
Computational methods for finding causal biomarkers and treatments for COVID-19	Current
Develop causal outcome prediction models for trustworthy interpretation	Current
Developing causal-based methods for recommending the repurposed drugs for a disease and applications in breast cancer and SARS-CoV-2	Current
Group and individual fairness in machine learning	Current
Integrative analyses of omics data for complex traits and diseases	Current
PAT Spectroscopic and MS techniques for near/real-time product characterisation for plasmaderived products	Current
Computational causal discovery from observational data and application in bioinformatics	Completed
Computational modelling for breast cancer prognosis in precision medicine	Completed
Dependency-based anomaly detection and applications	Completed
Developing data mining methods for finding causal relationships involving multiple factors	Completed
Developing network inference methods for cancer driver discovery	Completed
Intervention recommendation for disability employment service	Completed

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Associate Professor Thuc Le

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UniSA STEM

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Discovery Early Career Researcher Award

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PC Co-chair of Australasian Data Mining Conference

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Early Career Fellowship

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Professional Member

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Conference and Workshop Organiser

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Early Career Fellowship

HDR Thesis Examiner

Program Committee Member, Causality Workshop

Runner-up prize for DREAM challenge

Cancer Research Fund Raising Campaign

Interviewed by The LEAD South Australia about bioinformatics research and the success in PhD research thesis

Invited by the SA Governor as an SA emerging scientist to talk to the HRH The Duke of Kent during his visit to Australia

Teaching & student supervision

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