: Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninfor...
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasn...
Background: Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of n...
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...
This paper describes the development of an evolutionary algorithm called Multipopulation Cooperative Coevolutionary Programming (MCCP) that extends Genetic Programming (GP) to sea...
Background: High throughput gene expression experiments yield large amounts of data that can augment our understanding of disease processes, in addition to classifying samples. He...