Bio-Knowledge Engineering Research Laboratory

Institute for Chemical Research, Kyoto University

Gokasho, Uji, Kyoto, 611-0011, Japan

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

- 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". To appear in
*Briefings in Bioinformatics*, 2018. - 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. - N. Wicker, C.H. Nguyen, H. Mamitsuka, "Some Properties of a Dissimilarity Measure for Labeled Graphs".
*Publications Mathematiques de Besancon*. pp. 85-94, 2016. - 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. - 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. - 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. - 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. - 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. - 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. - 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. - 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. - 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. - 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. - C. H. Nguyen and T. B. Ho, "An efficient kernel matrix evaluation measure,"
*Pattern Recognition,*vol. 41, no. 11, pp. 3366-3372, 2008. - 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. - C. H. Nguyen and T. B. Ho, "Kernel matrix evaluation,"
*International Joint Conference on Artificial Intelligence (IJCAI2007),*pp. 987-992, 2007. - 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. - 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. - 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. - 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.