Background: In the microarray experiment, many undesirable systematic variations are commonly observed. Normalization is the process of removing such variation that affects the me...
Dankyu Yoon, Sung-Gon Yi, Ju-Han Kim, Taesung Park
Background: Stochastic dependence between gene expression levels in microarray data is of critical importance for the methods of statistical inference that resort to pooling test-...
Xing Qiu, Andrew I. Brooks, Lev Klebanov, Andrei Y...
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&...
Background: Oligonucleotide arrays have become one of the most widely used high-throughput tools in biology. Due to their sensitivity to experimental conditions, normalization is ...
Marc Hulsman, Anouk Mentink, Eugene P. van Someren...
Background: As an alternative to the frequently used "reference design" for two-channel microarrays, other designs have been proposed. These designs have been shown to b...
Ana C. Fierro, Raphael Thuret, Kristof Engelen, Gi...