Background Informative gene selection is of great importance in the analysis of microarray
expression data because of its huge dimensionality and relatively small samples, and also …

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 …

Microarray gene expression profile data is used to accurately predict different tumor types,
which has great value in providing better treatment and toxicity minimization on the patients …

With increasing interest in bioinformatics, sophisticated tools are required to efficiently
analyze gene information. The classification of gene expression profiles is crucial in those …

Gene expression profiles of 14 common tumors and their counterpart normal tissues were
analyzed with machine learning methods to address the problem of selection of tumor …

Previous studies on tumor classification based on feature extraction from gene expression
profiles (GEP) were proven to be effective, but some of such methods lack biomedical …

Selecting a subset of marker genes from thousands of genes is an important topic in
microarray experiments for diseases classification and prediction. In this paper, we …

Background To identify disease genes from these gene expression profiles is critically
important for disease, such as cancer, subtype discovery, diagnosis and pathology study …

OBJECTIVE: The type of data in microarray provides unprecedented amount of data. A
typical microarray data of ovarian cancer consists of the expressions of tens of thousands of …

Microarray data referencing gene expression profiles provide valuable answers to a variety
of problems, and contributes to advances in clinical medicine. Gene expression data …