English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62568/95224 (66%)
Visitors : 2528630      Online Users : 49
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/53533

    Title: Profiling time course expression of virus genes - An illustration of Bayesian inference under shape restrictions
    Authors: Chien, Li-Chu;Chang, I-Shou;Jiang, Shih-Sheng;Gupta, Pramod K.;Wen, Chi-Chung;Wu, Yuh-Jenn;Hsiung, Chao A.
    Contributors: 淡江大學數學學系
    Keywords: Baculovirus;Bernstein polynomials;genome-wide expression profile;Markov chain Monte Carlo;microarray experiments;shape restricted regression
    Date: 2009-12
    Issue Date: 2011-05-20 09:42:28 (UTC+8)
    Publisher: Beachwood: Institute of Mathematical Statistics
    Abstract: There have been several studies of the genome-wide temporal transcriptional program of viruses, based on microarray experiments, which are generally useful in the construction of gene regulation network. It seems that biological interpretations in these studies are directly based on the normalized data and some crude statistics, which provide rough estimates of limited features of the profile and may incur biases. This paper introduces a hierarchical Bayesian shape restricted regression method for making inference on the time course expression of virus genes. Estimates of many salient features of the expression profile like onset time, inflection point, maximum value, time to maximum value, area under curve, etc. can be obtained immediately by this method. Applying this method to a baculovirus microarray time course expression data set, we indicate that many biological questions can be formulated quantitatively and we are able to offer insights into the baculovirus biology.
    Relation: The Annals of Applied Statistics 3(4), pp.1542-1565
    DOI: 10.1214/09-AOAS258
    Appears in Collections:[Graduate Institute & Department of Mathematics] Journal Article

    Files in This Item:

    File Description SizeFormat
    1932-6157_3(4)_p1542-1565.pdf469KbAdobe PDF367View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback