Background Previous studies on tumor classification based on gene expression profiles
suggest that gene selection plays a key role in improving the classification performance …

The tumor diagnosis method based on gene expression profiles will be developed into the
fast and effective method in clinical domain in the near future. Although DNA microarray …

In high-dimensional gene expression data, selecting an optimal subset of genes is crucial
for achieving high classification accuracy and reliable diagnosis of diseases. This paper …

Background Gene expression data are often used to classify cancer genes. In such high-
dimensional datasets, however, only a few feature genes are closely related to tumors …

For the DNA microarray datasets, tumor classification based on gene expression profiles
has drawn great attention, and gene selection plays a significant role in improving the …

Background/Objectives: Accurate classification in cancer research is vital for devising
effective treatment strategies. Precise cancer classification depends significantly on …

Feature selection is an essential task to predict clinical risk and biomarkers from the gene
expression data. For practical matters, to choose the significant genes, researchers have …

Gene expression profiling reveals the activity of thousands of genes that can help to identify
cancer biomarkers. However, the presence of such a large number of genes in the profiles …

Gene expression profiling has played a significant role in the identification and classification
of tumor molecules. In gene expression data, only a few feature genes are closely related to …

Cancer is a highly heterogeneous disease caused by dysregulation in different cell types
and tissues. However, different cancers may share common mechanisms. It is critical to …