劉力瑜 副教授

國立台灣大學
農藝學系暨研究所生物統計組

辦公室: 農藝館 315 室
校址: 台北市(106)羅斯福路四段一號
電話傳真: 02-33664792
電子郵件: lyliu@ntu.edu.tw

Li-yu Daisy Liu

Associate Professor
Department of Agronomy, Biometry Division
National Taiwan University

No.1, Sec. 4, Roosevelt Road, Taipei, Taiwan 106
Office: Rm315, Department of Agronomy
Phone: +886-2-33664792
E-mail: lyliu@ntu.edu.tw


Education
  • B.S., Department of Agronomy, National Taiwan University, 1998
  • M.S., Department of Agronomy, National Taiwan University, 2000
  • Ph.D., Department of Statistics, Texas A&M University, 2005

    Courses I teach regularly
  • 統計應用軟體 (Statistical Computations and Analysis)
  • 試驗設計學 (Experimental Design)
  • 生物資訊學導論 (Introduction of Bioinformatics)
  • 作物基因體學 (Plant Genomics)

    Research interests:
  • Coefficient of intrinsic dependence (el CID):
    • Selecting relevant variables is a typical objective of various researches and is essential to statistical modeling. One of the major methods to select variables depends on the measures of associations. The coefficient of intrinsic dependence (CID) is a robust statistic to quantify the levels of association in general forms without distributional assumptions about the data. We are specifically interested in using CID to dissect complex gene regulatory networks.
      Selected publications
      1. Shen, Po-chih, Ai-ling Hour, Li-yu Daisy Liu* (2017). Microarray meta-analysis to explore abiotic stress-specific gene expression patterns in Arabidopsis. Botanical Studies, 58(1), 22.
      2. Ya-Chun Hsiao, Li-yu Daisy Liu* (2016). A Stepwise Approach of Finding Dependent Variables via Coefficient of Intrinsic Dependence. Journal of Computational Biology, 23(1), 42-55. http://homepage.ntu.edu.tw/~lyliu/pCID/
      3. Chen-An Tsai, Li-yu D Liu* (2013). Identifying Gene Set Association Enrichment using the Coefficient of Intrinsic Dependence. PLoS One, 8: e58851. http://homepage.ntu.edu.tw/~lyliu/GSAA/
      4. Liu L-YD, Chang L-Y, Kuo W-H, Hwa H-L, Shyu M-K, Chang K-J, Hsieh F-J.* (2012). In Silico Prediction for Regulation of Transcription Factors on Their Shared Target Genes Indicates Relevant Clinical Implications in a Breast Cancer Population. Cancer Informatics 11(8470Supplementaryfiles):113. http://homepage.ntu.edu.tw/~lyliu/multCID/
      5. Liu, L.Y.D., C.Y. Chen, M.J.M. Chen, M.S. Tsai, C.H.S. Lee, T.L. Phang, L.Y. Chang, W.H. Kuo, H.L. Hwa, H.C. Lien, S.M. Jung, Y.S. Lin, J.K. Chang, F.J. Hsieh* (2009). Statistical identification of gene association by CID in application of constructing ER regulatory network. BMC Bioinformatics 10: 85. (SCI) http://homepage.ntu.edu.tw/~lyliu/BC/
      6. Hsing, T., Liu, L.-Y., Brun, M., and Dougherty, E.R.* (2005). The coefficient of intrinsic dependence (feature selection using el CID). Pattern Recognition 38, 623-636.(SCI)
  • Gene exonization:
    • Insertion of transposable elements (TEs) into introns can lead to their activation as alternatively spliced cassette exons, an event called exonization which can enrich the complexity of transcriptomes and proteomes. We are studying the TE exonization in silico by inserting a TE into the introns of plant genes.
      Selected publications
      1. Yuh-Chyang Charng, Lung-Hsin Hsu, Li-yu Daisy Liu* (2017). The Ds1 transposon provides messages that yield unique profiles of protein isoforms and acts synergistically with Ds to enrich proteome complexity via exonization. Evolutionary Bioinformatics. 13, 1-11. (SCI).
      2. Ting-Ying Chien, Li-yu D Liu and Yuh-Chyang Charng* (2013). Analysis of New Functional Profiles of Protein Isoforms Yielded by Ds Exonization in Rice. Evolutionary Bioinformatics 9: 417-427.(SCI)
      3. Yuh-Chyang Charng, Li-yu D Liu* (2013). The extent of Ds1 transposon to enrich transcriptomes and proteomes by exonization. Botanical Studies, 54: 14. (SCI)
      4. Li-yu D Liu and Yuh-Chyang Charng. 2012. Genome-Wide Survey of Ds Exonization to Enrich Transcriptomes and Proteomes in Plants. Evolutionary Bioinformatics 8: 575-587.(SCI)
      5. Huang K-C, Yang H-C, Li K-T, Liu L-y, Charng Y-C (2012). Ds transposon is biased towards providing splice donor sites for exonization in transgenic tobacco. Plant Molecular Biology 79(4):509-519
  • Multiple environmental trial (MET) data analysis and crop modeling
    • Selected publications
      1. 劉力瑜, 陳丘原, 楊志維, 鄭佳綺, 吳炳奇, 張芯瑜, 丁文彥, 黃佳興, 呂秀英, 賴明信, 吳東鴻* (2016)。水稻產量區域試驗之 GGE 分析法雙軸圖例釋。作物、環境與生物資訊, 13: 167-178。
      2. 史凱萱, 陳凱儀, 呂秀英, 呂椿棠, 周國隆, 劉力瑜* (2014)。區域試驗多性狀產量指標之穩定性分析。作物、環境與生物資訊, 11: 80-87。
      3. 胡凱康, 劉力瑜* (2013)。多重環境試驗之直線迴歸穩定性統計法。作物、環境與生物資訊,10:131-142。
  • Next generation sequencing (NGS) data analysis
    • Selected publications
      1. 林書弘, 胡凱康, 劉力瑜* (2013)。次世代定序資料模擬軟體的比較。作物、環境與生物資訊, 10: 16-33。
      2. Yen-Yu Lin, Meng-Mei Fang, Pin-Chun Lin, Ming-Tzu Chiu, Li-yu D Liu, Chan-Pin Lin, and Shih-Shun Lin* (2013). Improving initial infectivity of the Turnip mosaic virus (TuMV) infectious clone by an mini binary vector via agro-infiltration. Botanical Studies. (SCI).
  • List of statistical sources in my field

  • Statistic Society
  • American Statistical Association
  • Institute of Mathematical Statistics
  • Current Index to Statistics