In the recent decades, researchers have introduced an abundance of feature selection
methods many of which are studied and analyzed over the high dimensional datasets …

Gene selection aims at identifying a (small) subset of informative genes from the initial data
in order to obtain high predictive accuracy for classification. Gene selection can be …

Gene expression profiles have great potential as a medical diagnosis tool because they
represent the state of a cell at the molecular level. In the classification of cancer type …

The emergence of DNA Microarray technology has enabled researchers to analyze the
expression level of thousands of genes simultaneously. The Microarray data analysis is the …

In this paper, we present two novel memetic algorithms (MAs) for gene selection. Both are
synergies of Genetic Algorithm (wrapper methods) and local search methods (filter methods) …

In recent times, microarray gene expression datasets have gained significant popularity due
to their usefulness to identify different types of cancer directly through bio-markers. These …

In DNA microarray datasets, the number of genes are very large, typically in thousands while
the number of samples are in hundreds. This raises the issue of generalization in the …

Identifying a small subset of informative genes from a gene expression dataset is an
important process for sample classification in the fields of bioinformatics and machine …

Recently, many methods have been proposed for microarray data analysis. One of the
challenges for microarray applications is to select a proper number of the most relevant …

Gene Expression is the process of determining the physical characteristics of living beings
by generating the necessary proteins. Gene Expression takes place in two steps, translation …