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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/93413


    Title: Prediction of Regulatory Gene Pairs Using Dynamic Time Warping and Gene Ontology
    Authors: Yang, Andy C.;Hsu, Hui-Huang;Lu, Ming-Da;Tseng, Vincent S.;Shih, Timothy K.
    Contributors: 淡江大學資訊工程學系
    Keywords: microarray time series data;missing value imputation;gene regulation prediction;DTW;dynamic time warping;gene ontology
    Date: 2013-12-01
    Issue Date: 2014-01-09 13:38:15 (UTC+8)
    Publisher: Olney: Inderscience Publishers
    Abstract: Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.
    Relation: International Journal of Data Mining and Bioinformatics 10(2), pp.121-145
    DOI: 10.1504/IJDMB.2014.064010
    Appears in Collections:[資訊工程學系暨研究所] 期刊論文

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