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Profiling time course expression of virus genes-an illustration of Bayesian inference under shape restrictions
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Profiling time course expression of virus genes-an illustration of Bayesian inference under shape restrictions

Li-Chu Chien, I-Shou Chang, Shih Sheng Jiang, Pramod K. Gupta, Chi-Chung Wen, Yuh-Jenn WuChao A. Hsiung
Annals of Applied Statistics, 卷.3(4), 頁碼.1542-1565
12/2009

摘要

Baculovirus Bernstein polynomials Genome-wide expression profile Markov chain Monte Carlo Microarray experiments Shape restricted regression Statistics and Probability Modeling and Simulation Statistics Probability and Uncertainty
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. © Institute of Mathematical Statistics, 2009.

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https://doi.org/10.1214/09-AOAS258檢視
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