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» Combined Gene Selection Methods for Microarray Data Analysis
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114
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BMCBI
2006
95views more  BMCBI 2006»
15 years 2 months ago
A simple method for assessing sample sizes in microarray experiments
In this short article, we discuss a simple method for assessing sample size requirements in microarray experiments. Our method starts with the output from a permutation-based anal...
Robert Tibshirani
92
Voted
BIOINFORMATICS
2007
66views more  BIOINFORMATICS 2007»
15 years 2 months ago
Gene expression network analysis and applications to immunology
We address the problem of using expression data and prior biological knowledge to identify differentially expressed pathways or groups of genes. Following an idea of Ideker et al...
Serban Nacu, Rebecca Critchley-Thorne, Peter Lee, ...
135
Voted
BIB
2007
59views more  BIB 2007»
15 years 2 months ago
Statistically designing microarrays and microarray experiments to enhance sensitivity and specificity
Gene expression signatures from microarray experiments promise to provide important prognostic tools for predicting disease outcome or response to treatment. A number of microarra...
Jason C. Hsu, Jane Chang, Tao Wang, Eiríkur...
151
Voted
BMCBI
2004
111views more  BMCBI 2004»
15 years 2 months ago
Multiclass discovery in array data
Background: A routine goal in the analysis of microarray data is to identify genes with expression levels that correlate with known classes of experiments. In a growing number of ...
Yingchun Liu, Markus Ringnér
152
Voted
BMCBI
2007
167views more  BMCBI 2007»
15 years 2 months ago
A stochastic differential equation model for transcriptional regulatory networks
Background: This work explores the quantitative characteristics of the local transcriptional regulatory network based on the availability of time dependent gene expression data se...
Adriana Climescu-Haulica, Michelle D. Quirk