Maximizing biomarker discovery by minimizing gene signatures.

ABSTRACT:

Background

The use of gene signatures can potentially be of considerable value in the field of clinical diagnosis. However, gene signatures defined with different methods can be quite various even when applied the same disease and the same endpoint. Previous studies have shown that the correct selection of subsets of genes from microarray data is key for the accurate classification of disease phenotypes, and a number of methods have been proposed for the purpose. However, these methods refine the subsets by only considering each single feature, and they do not confirm the association between the genes identified in each gene signature and the phenotype of the disease. We proposed an innovative new method termed Minimize Feature's Size (MFS) based on multiple level similarity analys

SUBMITTER: Chang C 

PROVIDER: S-EPMC3287502 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature