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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/75799


    Title: Imputing Missing Values in Microarray Data with Ontology Information
    Authors: Yang, Andy C.;Hsu, Hui-huang;Lu, Ming-da
    Contributors: 淡江大學資訊工程學系
    Keywords: Microarray;gene ontology;missing value
    Date: 2010-12-18
    Issue Date: 2012-04-16 09:39:04 (UTC+8)
    Abstract: Microarray technology is a big step in bioinformatics. Hidden information within the large amounts of data provides scientists with molecular functions or essential biological meanings to study and analyze. However, these data often contain a certain portion of entities that are missing. Several methods to estimate these missing values are developed, but most of them are with disadvantages. In this paper, we propose a novel approach to deal with these missing values based on a practical similarity measurement between gene pairs. Our approach takes gene expression values and gene ontology (GO) information for genes into consideration. We implement our approach on a real microarray dataset and compare its imputation accuracy with other methods. Experimental results show that our approach can estimate missing values in microarray data effectively.
    Relation: Proceeding of IEEE International Conference on Bioinformatics & Biomedicine Workshops (BIBM 2010), pp.535-540
    DOI: 10.1109/BIBMW.2010.5703858
    Appears in Collections:[資訊工程學系暨研究所] 會議論文

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