In efforts to discover disease mechanisms and improve clinical diagnosis of tumors, it is
useful to mine profiles for informative genes with definite biological meanings and to build …

Background Selecting a parsimonious set of informative genes to build highly generalized
performance classifier is the most important task for the analysis of tumor microarray …

The rapid development of DNA microarray technology enables researchers to measure the
expression levels of thousands of genes simultaneously and allows biologists easily gain …

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 …

Recent advanced technologies in DNA microarray analysis are intensively applied in
disease classification, especially for cancer classification. Most recent proposed gene …

Microarray gene expressions provide new opportunities for molecular classification of
heterogeneous diseases. Although various reported classification schemes show …

Two-gene classifiers have attracted a broad interest for their simplicity and practicality. Most
existing two-gene classification algorithms were involved in exhaustive search that led to …

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 …

For the purpose of improving the prediction of cancer prognosis in the clinical researches,
various algorithms have been developed to construct the predictive models with the gene …

Cancer diagnosis is an important emerging clinical application of microarray data. Its
accurate prediction to the type or size of tumors relies on adopting powerful and reliable …