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用于微小RNA靶标预测的计算方法。

Computational methods for microRNA target prediction.

作者信息

Watanabe Yuka, Tomita Masaru, Kanai Akio

机构信息

Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan.

出版信息

Methods Enzymol. 2007;427:65-86. doi: 10.1016/S0076-6879(07)27004-1.

Abstract

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.

摘要

微小RNA(miRNA)的发现为基因调控系统引入了一种新的模式。在广泛的物种中已鉴定出大量的miRNA,并且已知它们中的大多数通过miRNA与信使RNA(mRNA)的3'非翻译区(UTR)中的一个或多个特定位点的不完全结合来下调mRNA的翻译。广泛认为,鉴定miRNA靶向的基因是理解miRNA在基因调控网络中作用的重要一步。作为理解miRNA与其靶标之间相互作用的努力的一部分,已经基于观察到的诸如两个RNA分子之间的杂交程度等特征的规则开发了计算算法。这些计算机模拟方法为miRNA靶标检测提供了重要工具,并与实验验证一起,有助于揭示miRNA的调控靶标。在这里,我们总结了关于miRNA靶标识别原理以及当前可用的预测miRNA靶标基因的计算方法所积累的知识。

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