: Microarray data includes tens of thousands of gene expressions simultaneously, so it can be effectively used in identifying the phenotypes of diseases. However, the retrieval of ...
Dong-wan Hong, Jong-keun Lee, Sung-soo Park, Sang-...
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
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: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects...
Background: Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple ...