Han-Ming Wu - My Citations at Google Scholar
Journal Publications (main)
  1. Emily Chia-Yu Su, Han-Ming Wu*, (2023) Dimension reduction and visualization of multiple time series data: a symbolic data analysis approach,  Computational Statistics, 39, 1937-1969. (SCI)

  2. 陳逸瑄、王鴻龍、吳漢銘 ∗ (2023),象徵性資料分析法於電信信令資料的矩陣視覺化與分群, 中國統計學報, 61(2), 128-151.
  3. Wu, H.M. (2022), Book Review: Supervised Machine Learning for Text Analysis in R by Emil Hvitfeldt, Julia Silge, Biometrics, 78(3), 1270-1272.
  4. 張一凡、吳漢銘∗ (2021), 基於類別資訊的監督式t分布隨機鄰近嵌入法於維度縮減與視覺化之研究, 中國統計學報, 59(2), 53-97。
  5. Li, Y.Y. and Wu, H.M. (2019), Landmark isometric fuzzy sliced inverse regression with application to medical image segmentation, Journal of the Chinese Statistical Association, 57(1), 43-70.. [中文]
  6. 賴威宇、吳漢銘* (2018), 以維度縮減技術為基礎的互動式探索性資料分析平臺, 統計與資訊評論, 18卷, 19-48. [中文]
    (Lai, W.Y. and Wu, H. M., (2018), A web application for interactive exploratory data analysis based on dimension reduction techniques, Journal of Statistics and Computing, 18, 19-48.)
  7. Wu, H.M., Tien, Y.J., Ho, M.R., Hwu, H.G., Lin, W.C., Tao, M.H. and Chen, C.H. * (2018), Covariate-adjusted heatmaps for visualizing biological data via correlation decomposition, Bioinformatics, 34(20), 3529-3538. [SCI][Software]
  8. Kao, C.H., Nakano J., Shieh, S.H., Tien, Y.J., Wu, H.M., Yang, C.K., and Chen, C.H.* (2014), Exploratory data analysis of interval-valued symbolic data with matrix visualization, Computational Statistics & Data Analysis, 79, 14-29. [SCI]
  9. Chen, Y. S. and Wu, H. M.* (2013), The application of sliced inverse regression for dimension reduction of the interval-valued symbolic data, Journal of the Chinese Statistical Association, 51(3), 327-351. [中國統計學社101年論文優等獎] (NSC 101-2118-M-032-012)
  10. Yao, W. T. and Wu, H. M.* (2013). Isometric Sliced Inverse Regression for Nonlinear Manifolds Learning, Statistics and Computing, 23:563-576. [SCI]. (NSC 99-2118-M-032 -006)
  11. Wu, H. M.* (2011), On Biological Validity Indices for Soft Clustering Algorithms for Gene Expression Data, Computational Statistics and Data Analysis, 55(5), 1969-1979. [SCI]. [R code] (NSC 97-2118-M-032-001)
  12. Lu, H. H.-S*., and Wu, H. M. (2010), Visualization, Screening, and Classification of Cell Cycle-Regulated Genes in Yeast, International Journal of Systems and Synthetic Biology, 1(2), 185-198.  
  13. Wu, H. M., Tien, Y. J. and Chen, C. H.* (2010). GAP: A Graphical Environment for Matrix Visualization and Cluster Analysis, Computational Statistics and Data Analysis, 54, 767-778. [SCI] [Software]
  14. Wu, H. M.* (2008). Kernel Sliced Inverse Regression with Applications to Classification, Journal of Computational and Graphical Statistics 17(3), 590-610. [SCI] [Supplementary]
  15. Tien, Y. J., Lee, Y. S, Wu, H. M. and Chen, C. H.* (2008), Methods for Simultaneously Identifying Coherent Local Clusters with Smooth Global Patterns in Gene Expression Profiles. BMC Bioinformatics 9:155, 1-16. [SCI]
  16. Wu, H. M., and Lu, H. H.-S.* (2007), Iterative Sliced Inverse Regression for Segmentation of Ultrasound and MR Images, Pattern Recognition 40(12), 3492-3502. [SCI]
  17. Wu, H. M., and Lu, H. H.-S.* (2004), Supervised Motion Segmentation by Spatial-Frequential Analysis and Dynamic Sliced Inverse Regression, Statistica Sinica 14, 413-430. [SCI]
Journal Publications (Consulting) 
  1. Yin, S.Y., Wang, W.H., Wang, B.X., Aravindaram, K., Hwang, P.I., Wu, H.M. and Yang, N.S.* (2010), Stimulatory effect of Echinacea purpurea extract on the trafficking activity of mouse dendritic cells: revealed by genomic and proteomic analyses, BMC Genomics 11:612. [SCI]
  2. Lin, S.H., Liu, C.M., Liu, Y.L., Fann, C. S.J., Hsiao, P.C., Wu, J.Y., Hung, S.I., Chen, C.H., Wu, H.M., Jou, Y.S., Liu, S.K., Hwang, T.J., Hsieh, M.H., Chang, C.C., Yang, W.C., Lin, J.J., Chou, F.H.C., Faraone, S.V., Tsuang, M.T., Hwu, H.G.  and Chen, W.J. (2009), Clustering by Neurocognition for Fine Mapping of the Schizophrenia Susceptibility Loci on Chromosome 6p. Genes, Brain and Behavior 8(8):785-794. [SCI]
  3. Wang, C.Y., Staniforth, V., Chiao, M.T., Hou, C.C., Wu, H.M., Yeh, K.C., Chen, C.H., Hwang, P.I., Wen, T.N., Shyur, L.F., and Yang, N.S*. (2008), Genomics and Proteomics of Immune Modulatory Effects of a Butanol Fraction of Echinacea purpurea in Human Dendritic Cells. BMC Genomics 2008, 9:479. [SCI]
  4. Sher, Y. P., Chou, C. C., Chou, R. H., Wu, H. M., Chang, W. S., Chen, C. H., Wu, C. W., Yang, P. C., Yu, C. L., and Peck, K.* (2006), Human Kallikrein 8 Protease Confers a Favorable Clinical Outcome in Non–Small Cell Lung Cancer by Suppressing Tumor Cell Invasiveness, Cancer Research 66, 11763-11770. [SCI]
Conference Publications
  1. Wu, H.M., (2013),  On Visualization of Fuzzy Clustering Results, Proceedings of Joint Meeting of the IASC Satellite Conference and the 8th Conference of the Asian Regional Section of the IASC, pp.127-130.
  2. Wu, H.M. (2011), Nonlinear Extension of Sliced Inverse Regression using the Geodesic Distance Approximation, Proceedings of the Seventh IMT-GT International Conference on Mathematics, Statistics and its Applications (ICMSA 2011), pp. 312-322, July 21-23 2011, Bangkok Thailand. 
  3. Tzeng, S.L., Wu, H.M., and Chen, C.H.* (2009). Selection of Proximity Measures for Matrix Visualization of Binary Data, Proceedings of the 2009 2nd International Conference on BioMedical Engineering and Informatics (BMEI 2009), pp. 1932-1940, Tianjin, China. [EI]
  4. Chen, C. H.*, Hwu, H. G., Jang, W. J., Kao, C. H., Tien, Y. J., Tzeng, S., and Wu, H. M. (2004), Matrix Visualization and Information Mining, Proceedings in Computational Statistics 2004 (Compstat 2004), pp. 85-100, Physica-Verlag.
  5. Lu, H. H.-S.*, and Wu, H. M. (2003), On Visualization, Screening, and Classification of Cell Cycle-Regulated Genes in Yeast, The 14th International Conference on Genome Informatics (GIW2003), pp. 344-345.
Book Chapters
  1. Wu, H. M., Kao, C.H., Chen, C.H.* (2020), Dimension reduction and visualization of symbolic interval-valued data using sliced inverse regression, Book chapter in Advances in Data Science: Symbolic, Complex, and Network Data (Eds. Diday, E., Guan, R., Saporta, G., and Wang, H.). Wiley, pp. 49-78.
  2. Wu, H. M., Tzeng, S. and Chen, C. H.* (2006). Matrix Visualization. In Chun-houh Chen, Wolfgang Härdle, and Antony Unwin, editors, Handbook of Computational Statistics (Volume III): Data Visualization, Springer-Verlag, Heidelberg.
  1. Wu, H. M., and Chen, C.H.* (2020), Matrix visualization: a review and perspective, WIRES Computational Statistics.
  2. Wu, H. M. (2011).VisFuz: Visualization of Fuzzy Clustering Results in R.
  3. Wu, H. M. (2011). Iterative Fuzzy Sliced Inverse Regression for Unsupervised Segmentation of MR Brain Images.
  4. Hu, C. Y., Wu, H. M.* (2011). jSDRlib: A Java Library for Sufficient Dimension Reduction.
Conference Presentation
      • Wu, H. M. and Chen, C. H. (2004), Adjustment and Evaluation of Gene Expression Clustering Results Using Conditional Matrix Visualization, 2004 Taipei Symposium of Statistical Genome, December 2004.
      • Wu, H. M. (2004), Generalized Association Plots with a Covariate Adjustment, COMPSTAT 2004 Abstracts, 351. [The final ten commended posters from a total of more than 160 participants]
      • Wu, H. M., and Lu, H. H.-S. (2003), Statistical Applications of Dimension Reduction to Segmentation of Medical Images and Classification of Microarray Data, PhD Thesis. Institute of Statistics, National Chiao-Tung University.
      • Wu, H. M., and Shih, Y. S. (1997), Resampling Methods on Classification Trees, Master Thesis. Institute of Mathematical Statistics, National Chung -Cheng University.