Background: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories...
Homin K. Lee, William Braynen, Kiran Keshav, Paul ...
—This paper considers feature selection for data classification in the presence of a huge number of irrelevant features. We propose a new feature selection algorithm that addres...
Background: The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust ex...
Kevin A. Greer, Matthew R. McReynolds, Heddwen L. ...
DNA microarray experiments generate thousands of gene expression measurement simultaneously. Analyzing the difference of gene expression in cell and tissue samples is useful in dia...
Proper treatment of selections is essential in parametric feature-based design. Data exchange is one of the most important operators in any design paradigm. In this paper we addre...