Differential gene expression in disease: a comparison between high-throughput studies and the literature.

ABSTRACT:

Background

Differential gene expression is important to understand the biological differences between healthy and diseased states. Two common sources of differential gene expression data are microarray studies and the biomedical literature.

Methods

With the aid of text mining and gene expression analysis we have examined the comparative properties of these two sources of differential gene expression data.

Results

The literature shows a preference for reporting genes associated to higher fold changes in microarray data, rather than genes that are simply significantly differentially expressed. Thus, the resemblance between the literature and microarray data increases when the fold-change threshold for microarray data is increased. Moreover, the literature has a reportin

SUBMITTER: Rodriguez-Esteban R 

PROVIDER: S-EPMC5637346 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature