This paper proposes a novel method for gene selection. In the method, the gene regulation, an important mechanism of gene activities, is first introduced, and then the probabiliti...
In recent years, the rapid development of DNA Microarray technology has made it possible for scientists to monitor the expression level of thousands of genes in a single experiment...
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Background: In discriminant analysis of microarray data, usually a small number of samples are expressed by a large number of genes. It is not only difficult but also unnecessary ...
Background: Gene selection is an important step when building predictors of disease state based on gene expression data. Gene selection generally improves performance and identifi...
Carmen Lai, Marcel J. T. Reinders, Laura J. van't ...
Background: Selection of relevant genes for sample classification is a common task in most gene expression studies, where researchers try to identify the smallest possible set of ...
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: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Background: Microarray techniques survey gene expressions on a global scale. Extensive biomedical studies have been designed to discover subsets of genes that are associated with ...