| Literature DB >> 11847083 |
Abstract
A method that incorporates feature selection into Fisher's linear discriminant analysis for gene expression based tumor classification and a corresponding program Tclass were developed. The proposed method was applied to a public gene expression data set for colon cancer that consists of 22 normal and 40 tumor colon tissue samples to evaluate its performance for classification. Preliminary results demonstrated that using only a subset of genes ranging from 3 to 10 can achieve high classification accuracy.Entities:
Mesh:
Year: 2002 PMID: 11847083 DOI: 10.1093/bioinformatics/18.2.325
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937