Accurate and robust gene selection for disease classification using a simple statistic.
Discrimination of disease patients based on gene expression data is a crucial problem in clinical area. An important issue to solve this problem is to find a discriminative subset of genes from thousands of genes on a microarray or DNA chip. Aiming at finding informative genes for disease classification on microarray, we present a gene selection method based on the forward variable (gene) selection method (FSM) and show, using typical public microarray datasets, that our method can extract a small set of genes being crucial for discriminating different classes with a very high accuracy almost closed to perfect classification.
Mutsubayashi
Hikaru
H
Division of Production and Information Systems Engineering, Muroran Institute of Technology, Mizumoto, Muroran, Japan.
Aso
Seiichiro
S
Nagashima
Tomomasa
T
Okada
Yoshifumi
Y