Background: DNA microarrays, which determine the expression levels of tens of thousands of genes from a sample, are an important research tool. However, the volume of data they pr...
Alexander L. Richards, Peter Holmans, Michael C. O...
Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive exp...
Background: Large-scale genomic studies often identify large gene lists, for example, the genes sharing the same expression patterns. The interpretation of these gene lists is gen...
Xin He, Moushumi Sen Sarma, Xu Ling, Brant W. Chee...
Background: Due to the large number of genes in a typical microarray dataset, feature selection looks set to play an important role in reducing noise and computational cost in gen...
Background: Numerous feature selection methods have been applied to the identification of differentially expressed genes in microarray data. These include simple fold change, clas...