Microarray experiments produce gene expression data at such a high speed and volume that it is imperative to use highly specialized computational tools for their analyses. One grou...
Dong-Guk Shin, John Bluis, Yoo Ah Kim, Winfried Kr...
Background: Statistical methods for ranking differentially expressed genes (DEGs) from gene expression data should be evaluated with regard to high sensitivity, specificity, and r...
Background: Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analys...
Background: With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis...
Background: Microarray data normalization is an important step for obtaining data that are reliable and usable for subsequent analysis. One of the most commonly utilized normaliza...
John A. Berger, Sampsa Hautaniemi, Anna-Kaarina J&...