Classification of genes and putative biomarker identification using distribution metrics on expression profiles.

ABSTRACT:

Background

Identification of genes with switch-like properties will facilitate discovery of regulatory mechanisms that underlie these properties, and will provide knowledge for the appropriate application of Boolean networks in gene regulatory models. As switch-like behavior is likely associated with tissue-specific expression, these gene products are expected to be plausible candidates as tissue-specific biomarkers.

Methodology/principal findings

In a systematic classification of genes and search for biomarkers, gene expression profiles (GEPs) of more than 16,000 genes from 2,145 mouse array samples were analyzed. Four distribution metrics (mean, standard deviation, kurtosis and skewness) were used to classify GEPs into four categories: predominantly-off, predominantly-on,

SUBMITTER: Huang HC 

PROVIDER: S-EPMC2816221 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature