Computational Challenges in miRNA Target Predictions: To Be or Not to Be a True Target?. (4th May 2009)

• Record Type: Journal Article
• Authors: Barbato, Christian; Arisi, Ivan; Frizzo, Marcos E.; Brandi, Rossella; Da Sacco, Letizia; Masotti, Andrea
• Other Names: Ghosh Zhumur Academic Editor.
• Is Part Of: Journal of biomedicine and biotechnology. Volume 2009(2009)
• Publication Date: 2009-05-04
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Medicine; Biology; Biotechnology; Médecine; Biologie; Biotechnologie; Biology; Biotechnology; Medicine; Biotechnology; Biomedicine; Electronic journals; Periodical; Periodicals; Electronic journals; 610
• DOI: 10.1155/2009/803069
• Languages: English
• ISSNs: 1110-7243

Abstract

Abstract : All microRNA (miRNA) target—finder algorithms return lists of candidate target genes. How valid is that output in a biological setting? Transcriptome analysis has proven to be a useful approach to determine mRNA targets. Time course mRNA microarray experiments may reliably identify downregulated genes in response to overexpression of specific miRNA. The approach may miss some miRNA targets that are principally downregulated at the protein level. However, the high-throughput capacity of the assay makes it an effective tool to rapidly identify a large number of promising miRNA targets. Finally, loss and gain of function miRNA genetics have the clear potential of being critical in evaluating the biological relevance of thousands of target genes predicted by bioinformatic studies and to test the degree to which miRNA-mediated regulation of any "validated" target functionally matters to the animal or plant.