@inproceedings{a0aa4f227b594951acbfcf206a2edabb,
title = "Bayesian hierarchical models for serial analysis of gene expression",
abstract = "In the Serial Analysis of Gene Expression (SAGE) analysis, the statistical procedures have been performed after aggregation of observations from the various libraries for the same class. Most studies have not accounted for the within-class variability. The identification of the differentially expressed genes based on the class separation has not been easy because of heteroscedasticity of libraries. We propose a hierarchical Bayesian model that accounts for the within-class variability. The differential expression is measured by a distribution-free silhouette width which was first introduced into the SAGE differential expression analysis. It is shown that the silhouette width is more appropriate and is easier to compute than the error rate.",
keywords = "Bayesian hierarchical model, SAGE, Serial analysis of gene expression",
author = "Seungyoon Nam and Seungmook Lee and Sanghyuk Lee and Seokmin Shin and Taesung Park",
year = "2006",
doi = "10.1007/11960669_4",
language = "English",
isbn = "3540689702",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "29--39",
booktitle = "Data Mining and Bioinformatics - First International Workshop, VDMB 2006, Revised Selected Papers",
note = "1st International Workshop on Data Mining and Bioinformatics, VDMB 2006 ; Conference date: 11-09-2006 Through 11-09-2006",
}