Computational methods for microRNA target prediction

• Published in: Methods in enzymology Vol. 427; p. 65
• Main Authors: Watanabe, Yuka, Tomita, Masaru, Kanai, Akio
• Format: Journal Article
• Language: English
• Published: United States 2007
• Subjects: Computational Biology; MicroRNAs - genetics
• ISSN: 0076-6879
• DOI: 10.1016/s0076-6879(07)27004-1

The discovery of microRNAs (miRNAs) has introduced a new paradigm into gene regulatory systems. Large numbers of miRNAs have been identified in a wide range of species, and most of them are known to downregulate translation of messenger RNAs (mRNAs) via imperfect binding of the miRNA to a specific site or sites in the 3' untranslated region (UTR) of the mRNA. Identification of genes targeted by miRNAs is widely believed to be an important step toward understanding the role of miRNAs in gene regulatory networks. As part of the effort to understand interactions between miRNAs and their targets, computational algorithms have been developed based on observed rules for features such as the degree of hybridization between the two RNA molecules. These in silico approaches provide important tools for miRNA target detection, and together with experimental validation, help to reveal regulated targets of miRNAs. Here, we summarize the knowledge that has been accumulated about the principles of target recognition by miRNAs and the currently available computational methodologies for prediction of miRNA target genes.