: In most studies concerning expression data analyses information on the variability of gene intensity across samples is usually exploited. This information is sensitive to initial...
Alexey V. Antonov, Igor V. Tetko, Denis Kosykh, Di...
Background: With DNA microarray data, selecting a compact subset of discriminative genes from thousands of genes is a critical step for accurate classification of phenotypes for, ...
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
Achieving high classification accuracy is a major challenge in the diagnosis of cancer types based on gene expression profiles. These profiles are notoriously noisy in that a larg...
Background: Many classification approaches have been applied to analyzing transcriptional regulation of gene expressions. These methods build models that can explain a gene's...