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 ...
Gene Expression Programming (GEP) aims at discovering essential rules hidden in observed data and expressing them mathematically. GEP has been proved to be a powerful tool for cons...
Lei Duan, Changjie Tang, Tianqing Zhang, Dagang We...
Microarray data usually contains a high level of noisy gene data, the noisy gene data include incorrect, noise and irrelevant genes. Before Microarray data classification takes pla...
Several microarray technologies that monitor the level of expression of a large number of genes have recently emerged. Given DNA-microarray data for a set of cells characterized b...
We describe our contribution to the ICMLA2008 "Automated Micro-Array Classification Challenge". The design of our classifier is motivated by the special scenario encounte...
Donald Geman, Bahman Afsari, Aik Choon Tan, Daniel...