Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are common...
Pengyi Yang, Bing Bing Zhou, Zili Zhang, Albert Y....
Background: With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Suc...
Ki-Yeol Kim, Dong Hyuk Ki, Ha Jin Jeong, Hei-Cheul...
Background: The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. Wh...
Junhee Seok, Amit Kaushal, Ronald W. Davis, Wenzho...
Background: When conducting multiple hypothesis tests, it is important to control the number of false positives, or the False Discovery Rate (FDR). However, there is a tradeoff be...
Background: A large number of papers have been published on analysis of microarray data with particular emphasis on normalization of data, detection of differentially expressed ge...