A Unified Mixed Effects Model for Gene Set Analysis of Time Course Microarray Experiments
نویسندگان
چکیده
منابع مشابه
Significance analysis of time course microarray experiments.
Characterizing the genome-wide dynamic regulation of gene expression is important and will be of much interest in the future. However, there is currently no established method for identifying differentially expressed genes in a time course study. Here we propose a significance method for analyzing time course microarray studies that can be applied to the typical types of comparisons and samplin...
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با توجه به تجزیه و تحلیل داده ها ما دریافتیم که سطح درامد و تعداد نمایندگیها باتقاضای بیمه عمر رابطه مستقیم دارند و نرخ بهره و بار تکفل با تقاضای بیمه عمر رابطه عکس دارند
Time-Course Gene Set Analysis for Longitudinal Gene Expression Data
Gene set analysis methods, which consider predefined groups of genes in the analysis of genomic data, have been successfully applied for analyzing gene expression data in cross-sectional studies. The time-course gene set analysis (TcGSA) introduced here is an extension of gene set analysis to longitudinal data. The proposed method relies on random effects modeling with maximum likelihood estima...
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Environmental and evolutionary biologists have recently benefited from advances in experimental design and statistical analysis for complex gene expression microarray experiments. The high-throughput time course experiment highlights gene function by uncovering functionally similar responses across varied experimental conditions. Since these time-dependent responses can be compared across phylo...
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Microarrays are powerful tools for surveying the expression levels of many thousands of genes simultaneously. They belong to the new genomics technologies which have important applications in the biological, agricultural and pharmaceutical sciences. There are myriad sources of uncertainty in microarray experiments, and rigorous experimental design is essential for fully realizing the potential ...
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ژورنال
عنوان ژورنال: Statistical Applications in Genetics and Molecular Biology
سال: 2009
ISSN: 1544-6115
DOI: 10.2202/1544-6115.1484