Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
Background: Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant info...
Anup Parikh, Eryong Huang, Christopher Dinh, Blaz ...
Background: High-throughput sequencing technologies, such as the Illumina Genome Analyzer, are powerful new tools for investigating a wide range of biological and medical question...
James H. Bullard, Elizabeth Purdom, Kasper D. Hans...
Background: Expression microarrays are increasingly used to characterize environmental responses and hostparasite interactions for many different organisms. Probe selection for cD...
Yian A. Chen, David J. Mckillen, Shuyuan Wu, Matth...
This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximi...