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计算方法及相关工具在物种中识别 microRNA:鸟瞰图。

Computational Approaches and Related Tools to Identify MicroRNAs in a Species: A Bird's Eye View.

机构信息

Centre for Bioinformatics, Pondicherry University, Pondicherry, 605014, India.

Department of Pathology, Dunedin School of Medicine, University of Otago, 270 Great King Street, Dunedin, 9054, New Zealand.

出版信息

Interdiscip Sci. 2018 Sep;10(3):616-635. doi: 10.1007/s12539-017-0223-x. Epub 2017 Mar 30.

Abstract

MicroRNAs (miRNAs) are a family of non-coding RNAs that play a central role in fine-tuning gene expression regulation. Over the past decade, identification and annotation of miRNAs have become a major focus in epigenomics research. However, detection and characterization of miRNA are challenging due to its small size (~22 nucleotide-long) and susceptibility to degradation. The difficulties involved in experimental prediction and characterization of miRNA coding genes have led to the development of in silico-based approaches. Although several algorithms have been developed in recent years, a comprehensive assessment of the principles, methodological insights, and estimate of the strengths and weaknesses of computational methods are limited. The present review is dealt with the detailed methodological insights of different tools used for identifying miRNA coding genes falling under four computational approaches. The parameters considered in these tools along with their specificity are also delineated. Furthermore, the strengths and weaknesses of these four computational approaches, and the bioinformatics resources pertaining to target identification, expression analysis, regulatory network analysis, and SNP identification are stated in this review. The methodological details of miRNA prediction methods and bioinformatics resources related to miRNA research in one platform would facilitate the miRNA research community to develop efficient tools for uncovering novel miRNAs and understanding their role in regulatory networks.

摘要

微小 RNA(miRNA)是一类非编码 RNA,在精细调控基因表达调节中起着核心作用。在过去的十年中,miRNA 的鉴定和注释已成为表观基因组学研究的主要焦点。然而,由于 miRNA 体积小(~22 个核苷酸长)且易降解,因此其检测和特征分析具有挑战性。由于 miRNA 编码基因的实验预测和特征分析具有难度,因此开发了基于计算的方法。尽管近年来已经开发了几种算法,但对计算方法的原理、方法学见解以及对其优缺点的评估仍很有限。本综述详细介绍了用于识别属于四种计算方法的 miRNA 编码基因的不同工具的方法学见解。还描述了这些工具中考虑的参数及其特异性。此外,在本文中还陈述了这四种计算方法的优缺点,以及与靶标识别、表达分析、调控网络分析和 SNP 识别相关的生物信息学资源。在一个平台中 miRNA 预测方法和 miRNA 研究相关的生物信息学资源的方法学细节将有助于 miRNA 研究界开发有效的工具,以揭示新的 miRNA 并了解它们在调控网络中的作用。

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