The DIANA-mirExTra web server: from gene expression data to microRNA function.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 20161787.
- Also identified by DOI 10.1371/journal.pone.0009171 and PMC identifier 2820085.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
BACKGROUND: High-throughput gene expression experiments are widely used to identify the role of genes involved in biological conditions of interest. MicroRNAs (miRNA) are regulatory molecules that have been functionally associated with several developmental programs and their deregulation with diverse diseases including cancer. METHODOLOGY/PRINCIPAL FINDINGS: Although miRNA expression levels may not be routinely measured in high-throughput experiments, a possible involvement of miRNAs in the deregulation of gene expression can be computationally predicted and quantified through analysis of overrepresented motifs in the deregulated genes 3' untranslated region (3'UTR) sequences. Here, we introduce a user-friendly web-server, DIANA-mirExTra (www.microrna.gr/mirextra) that allows the comparison of frequencies of miRNA associated motifs between sets of genes that can lead to the identification of miRNAs responsible for the deregulation of large numbers of genes. To this end, we have investigated different approaches and measures, and have practically implemented them on experimental data. CONCLUSIONS/SIGNIFICANCE: On several datasets of miRNA overexpression and repression experiments, our proposed approaches have successfully identified the deregulated miRNA. Beyond the prediction of miRNAs responsible for the deregulation of transcripts, the web-server provides extensive links to DIANA-mirPath, a functional analysis tool incorporating miRNA targets in biological pathways. Additionally, in case information about miRNA expression changes is provided, the results can be filtered to display the analysis for miRNAs of interest only.
Medical subject headings
- Computational Biology
- Gene Expression Profiling
- MicroRNAs
- Software