Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
In this work, we address the biclustering of gene expression data with evolutionary computation, which has been proven to have excellent performance on complex problems. In express...
Background: Advances in DNA microarray technology portend that molecular signatures from which microarray will eventually be used in clinical environments and personalized medicin...
Zhenqiang Su, Huixiao Hong, Hong Fang, Leming M. S...
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. ...
Abstract. This paper presents a method that uses gene ontologies, together with the paradigm of relational subgroup discovery, to help find description of groups of genes different...