Literature-aided meta-analysis of microarray data: a compendium study on muscle development and disease.

ABSTRACT:

Background

Comparative analysis of expression microarray studies is difficult due to the large influence of technical factors on experimental outcome. Still, the identified differentially expressed genes may hint at the same biological processes. However, manually curated assignment of genes to biological processes, such as pursued by the Gene Ontology (GO) consortium, is incomplete and limited. We hypothesised that automatic association of genes with biological processes through thesaurus-controlled mining of Medline abstracts would be more effective. Therefore, we developed a novel algorithm (LAMA: Literature-Aided Meta-Analysis) to quantify the similarity between transcriptomics studies. We evaluated our algorithm on a large compendium of 102 microarray studies published in the

SUBMITTER: Jelier R 

PROVIDER: S-EPMC2459190 | biostudies-literature | 2008 Jun

REPOSITORIES: biostudies-literature