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Journal of Biomedicine and Biotechnology
Volume 2009, Article ID 803069, 9 pages
http://dx.doi.org/10.1155/2009/803069
Review Article

Computational Challenges in miRNA Target Predictions: To Be or Not to Be a True Target?

1European Brain Research Institute-Fondazione EBRI-Rita Levi-Montalcini, Via del Fosso di Fiorano, 64/65, 00143 Roma, Italy
2Neurogenomics Facility, European Brain Research Institute-Fondazione EBRI-Rita Levi-Montalcini, Via del Fosso di Fiorano, 64/65, 00143 Roma, Italy
3Departamento de Ciências Morfológicas, ICBS, UFRGS, Rua Sarmento Leite 500, Porto Alegre, RS, CEP 90050-170, Brazil
4Gene Expression - Microarrays Laboratory, Bambino Gesù Children's Hospital, P.za S.Onofrio 4, 00165 Roma, Italy

Received 2 January 2009; Accepted 20 March 2009

Academic Editor: Zhumur Ghosh

Copyright © 2009 Christian Barbato et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.