Canh Hao Nguyen

Senior Lecturer

Bio-Knowledge Engineering Research Laboratory

Institute for Chemical Research, Kyoto University

Gokasho, Uji, Kyoto, 611-0011, Japan

Email: $myaccoutname @kuicr.kyoto-u.ac.jp

Research

 I am interested in Machine Learning in/for Bioinformatics, specially Machine Learning on Graphs. I am working on models for underlying mechanisms of biological networks.

Publication
  1. P. Petschner, A.D. Nguyen, C.H. Nguyen, H. Mamitsuka, "Machine learning for predicting drug- drug interactions: Graph neural networks and beyond", Current Opinion in Systems Biology, vol. 42, 100551, 2025.
  2. J. Lee, C.H. Nguyen, H. Mamitsuka, "Beyond rigid docking: deep learning approaches for fully flexible protein-ligand interactions", Briefings in Bioinformatics, vol. 26 (5):bbaf454, 2025.
  3. M. Ishikawa, Z. Jiang, C.H. Nguyen, H. Hatsukawa, T. Hirai, H. Matsumoto, E. Saito, K. Okazaki, K. Endo, S. Terada, H. Mamitsuka, "Uncovering Key Features for Predicting Comorbid Chronic Eosinophilic Pneumonia in Chronic Rhinosinusitis via Machine Learning", International Forum of Allergy & Rhinology, e23613, 2025.
  4. M. Ishikawa, Z. Jiang, C.H. Nguyen, H. Hatsukawa, H. Mamitsuka, "Clinical Key Features Uncovered by Blood Eosinophilia-Based Machine Learning Classification of Chronic Rhinosinusitis", International Forum of Allergy & Rhinology, 2025.
  5. S.H. Nguyen, D.Q. Le, T.T. Nguyen, C.H. Nguyen, T.H. Ho, N.S. Vo, T. Nguyen, H.A. Nguyen, M.D. Cao, "PanKA: Leveraging population pangenome to predict antibiotic resistance" iScience, vol. 27 (9), 110623, 2024.
  6. D.Q. Le, T.A. Nguyen, S.H. Nguyen, T.T. Nguyen, C.H. Nguyen, H.T. Phung, T.H. Ho, N.S. Vo, T. Nguyen, H.A. Nguyen, M.D. Cao, "Efficient inference of large prokaryotic pangenomes with PanTA", Genome Biology, vol. 21 (1), 209, 2024.
  7. D.Q. Le, S.H. Nguyen, T.T. Nguyen, C.H. Nguyen, T.H. Ho, N.S. Vo, T. Nguyen, H.A. Nguyen, M.D. Cao, "AMRViz enables seamless genomics analysis and visualization of antimicrobial resistance", BMC bioinformatics, vol. 25(1), 193, 2024.
  8. T. Cao, L. Sun, C.H. Nguyen, H. Mamitsuka, "Learning Low-Rank Tensor Cores with Probabilistic l0-Regularized Rank Selection for Model Compression", Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI-24), pp. 3780-3788, 2024.
  9. D.Q. Le, T.T. Nguyen, C.H. Nguyen, T.H. Ho, N.S. Vo, T. Nguyen, H.A. Nguyen, M.D. Cao, S.H. Nguyen, "AMRomics: a scalable workflow to analyze large microbial genome collections", BMC Genomics vol. 25 (1), n.709, 2024.
  10. V.H. Do, S.H. Nguyen, D.Q. Le, T.T. Nguyen, C.H. Nguyen, T.H. Ho, N.S. Vo, T. Nguyen, H.A. Nguyen, M.D. Cao, "Pasa: leveraging population pangenome graph to scaffold prokaryote genome assemblies", Nucleic acids research, vol. 52 (3), pp. e15, 2024.
  11. X. Wang, L. Sun, C.H. Nguyen and H. Mamitsuka, "Multiplicative Sparse Tensor Factorization for Multi-View Multi-Task Learning", Frontiers in Artificial Intelligence and Applications, 372: ECAI 2023 pp. 2560-2567, 2023.
  12. D.A. Nguyen, C.H. Nguyen, H. Mamitsuka, "Central-Smoothing Hypergraph Neural Networks for Predicting Drug-Drug Interactions", IEEE Transactions on Neural Networks and Learning Systems, vol. 35 (8), pp. 11620-11625, 2023 pdf
  13. C.H. Nguyen, "Semi-Supervised Learning on Large Graphs: is Poisson Learning a Game-Changer?", arXiv:2202.13608v2 [stat.ML]
  14. D.A. Nguyen, C.H. Nguyen, P. Petschner, H. Mamitsuka, "SPARSE: a sparse hypergraph neural network for learning multiple types of latent combinations to accurately predict drug-drug interactions", Bioinformatics, (ISMB 2022), vol. 38, no. 1, pp. i333-i341 pdf
  15. C.H. Nguyen, H. Mamitsuka, "On Convex Clustering Solutions", arXiv:2105.08348v1 [stat.ML]
  16. D.H. Nguyen, C.H. Nguyen, H. Mamitsuka, "Learning subtree pattern importance for Weisfeiler-Lehman based graph kernels". Machine Learning, vol. 10, no. 7, pp. 1585-1607, 2021. pdf
  17. D. A. Nguyen, K. A. Nguyen, C. H. Nguyen, K. Than, "Boosting prior knowledge in streaming variational Bayes", Neurocomputing, vol. 424, pp. 143-159, 2021. pdf
  18. M. Cai, C. H. Nguyen, H. Mamitsuka, L. Li, "XGSEA: CROSS-species Gene Set Enrichment Analysis via domain adaptation". Briefings in Bioinformatics, vol. 22, no. 5, 2021. pdf
  19. H. Kaneko et. al., "Eukaryotic virus composition can predict the efficiency of carbon export in the global ocean", iScience, vol. 24, no. 1, 2021. html
  20. D. A., Nguyen, C. H., Nguyen and H. Mamitsuka, "A Survey on Adverse Drug Reaction Studies: Data, Tasks, and Machine Learning Methods", Briefings in Bioinformatics, vol. 22, no 1, pp. 164-177 , 2021. pdf
  21. C. H. Nguyen, "Structured Learning in Biological Domain", Journal of Systems Science and Systems Engineering , vol.29, no. 4, pp 440-453, 2020. html
  22. C. H. Nguyen and H. Mamitsuka, "Learning on Hypergraphs with Sparsity", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, pp. 2710-2722, Aug. 2021. pdf
  23. L. Sun, C.H. Nguyen, H. Mamitsuka, "Fast and Robust Multi-View Multi-Task Learning via Group Sparsity", in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), pp. 3499-3505, 2019. pdf supplementary
  24. L. Sun, C.H. Nguyen, H. Mamitsuka, "Multiplicative Sparse Feature Decomposition for Efficient Multi-View Multi-Task Learning", in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), pp. 3506-3512, 2019. pdf supplementary
  25. D.H. Nguyen, C.H. Nguyen, H. Mamitsuka, "ADAPTIVE: leArning DAta-dePendenT, concIse molecular VEctors for fast, accurate metabolite identification from tandem mass spectra". Bioinformatics 35, (Proceedings of the 26th International Conference on Intelligent Systems for Molecular Biology (ISMB 2019), vol. 23, no. 14, pp. i164-i172 pdf
  26. H., Seki, C.H., Nguyen, V.-N., Huynh, M., Inuiguchi (Eds.) Integrated Uncertainty in Knowledge Modelling and Decision Making Proceedings of 7th International Symposium, IUKM 2019, Springer LNCS 11471, 2019. html
  27. N. Wicker, C.H. Nguyen, H. Mamitsuka, "A p-Laplacian random walk: application to video games". Austrian Journal of Statistics, vol. 48, no. 5, pp. 11-16, 2019. pdf
  28. D.H. Nguyen, C.H. Nguyen, H. Mamitsuka, "Recent advances and prospects of computational methods for metabolite identification: a review with emphasis on machine learning approaches", Briefings in Bioinformatics, vol. 20, no. 6, pp. 2028-2043, 2019. pdf
  29. D.H. Nguyen, C.H. Nguyen, H. Mamitsuka, "SIMPLE: Sparse Interaction Model over Peaks of MoLEcules for Fast, Interpretable Metabolite Identification from Tandem Mass Spectra".Bioinformatics, (Proceedings of the 26th International Conference on Intelligent Systems for Molecular Biology (ISMB 2018), pp. i323-i332, 2018. pdf
  30. N. Wicker, C.H. Nguyen, H. Mamitsuka, "Some Properties of a Dissimilarity Measure for Labeled Graphs". Publications Mathematiques de Besancon. pp. 85-94, 2016. pdf
  31. A. Mohamed, C.H. Nguyen, H. Mamitsuka, "NMRPro: An integrated web component for interactive processing and visualization of NMR spectra." Bioinformatics, vol. 32, no. 13, pp. 2067-2068, 2016. pdf
  32. C.H. Nguyen, H. Mamitsuka, "New Resistance Distances with Global Information on Large Graphs". JMLR Workshop and Conference Proceedings. Volume 51: Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, pp. 639-647, May 2016. pdf supplementary
  33. A. Mohamed, C.H. Nguyen, H. Mamitsuka, "Current status and prospects of computational resources for natural product dereplication: A review" Briefings in Bioinformatics, vol. 17, no. 2, pp. 309-321, 2016. pdf
  34. A. Mohamed, T. Hancock, C.H. Nguyen, H. Mamitsuka, "NetPathMiner: R/Bioconductor package for network path mining through gene expression", Bioinformatics. vol. 30, no. 21, pp. 3139-3141, Nov 01, 2014. pdf
  35. C. H. Nguyen, N. Wicker and H. Mamitsuka, "Selecting Graph Cut Solutions via Global Graph Similarity", IEEE Transactions on Neural Networks and Learning Systems. vol. 25, no. 7, pp. 1407-1412, 2014. pdf
  36. N. Wicker, C. H. Nguyen and H. Mamitsuka, "A new dissimilarity measure for comparing labeled graphs", Linear Algebra and its Applications. vol. 438, no. 5, pp. 2331-2338. Mar 01, 2013. pdf
  37. C. H. Nguyen and H. Mamitsuka, "Latent Feature Kernels for Link Prediction on Sparse Graphs" IEEE Transactions on Neural Networks and Learning Systems. vo. 23, no. 11, pp. 1793-1804, 2012. pdf
  38. C. H. Nguyen and H. Mamitsuka, "Kernels for link prediction with latent feature models," The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (2) (ECML/PKDD 2011), pp. 517-532, 2011. pdf
  39. C. H. Nguyen and H. Mamitsuka, "Discriminative graph embedding for label propagation," IEEE Transactions on Neural Networks, vol. 22, no. 9, pp. 1395-1405, 2011. pdf
  40. C. H. Nguyen, T. B. Ho, and V. Kreinovich, "Estimating quality of support vector machines learning under probabilistic and interval uncertainty: Algorithms and computational complexity," Interval / Probabilistic Uncertainty and Non-Classical Logics, pp. 57-69, 2008. pdf
  41. C. H. Nguyen and T. B. Ho, "An efficient kernel matrix evaluation measure," Pattern Recognition, vol. 41, no. 11, pp. 3366-3372, 2008. pdf
  42. H. Tanabe, T. B. Ho, C. H. Nguyen, and S. Kawasaki, "Simple but effective methods for combining kernels in computational biology," RIVF, pp. 71-78, 2008. pdf
  43. C. H. Nguyen and T. B. Ho, "Kernel matrix evaluation," International Joint Conference on Artificial Intelligence (IJCAI2007), pp. 987-992, 2007. pdf
  44. T. B. Ho, C. H. Nguyen, S. Kawasaki, S. Q. Le, and K. Takabayashi, "Exploiting temporal relations in mining hepatitis data," New Generation Computing, vol. 25, no. 3, pp. 247-262, 2007. pdf
  45. T. B. Ho, C. H. Nguyen, S. Kawasaki, and K. Takabayashi, "Temporal relations extraction in mining hepatitis data," The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2007), pp. 523-530, 2007.
  46. C. H. Nguyen and T. B. Ho, "Sampling for imbalanced data learning," The International Workshop on Data-Mining and Statistical Science (DMSS2006), pp. 12-19, 2006.
  47. C. H. Nguyen and T. B. Ho, "An imbalanced data rule learner," The European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD2005), pp. 617-624, 2005. pdf