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使用StructRNAfinder预测核苷酸序列中的RNA家族。

Predicting RNA Families in Nucleotide Sequences Using StructRNAfinder.

作者信息

Maracaja-Coutinho Vinicius, Arias-Carrasco Raúl, Nakaya Helder I, Aliaga-Tobar Victor

机构信息

Facultad de Ciencias Químicas y Farmacéuticas, Advanced Center for Chronic Diseases-ACCDiS, Universidad de Chile, Santiago, Chile.

Beagle Bioinformatics, Santiago, Chile.

出版信息

Methods Mol Biol. 2019;1962:15-27. doi: 10.1007/978-1-4939-9173-0_2.

Abstract

Noncoding RNA (ncRNA) research is already a routine in every genomics or transcriptomics initiatives. According to their functions, ncRNAs can be grouped into several different RNA families, which can be represented by conserved primary sequences, secondary structures, or covariance models (CMs). CMs are very sensitive in predicting RNA families in nucleotide sequences and have been widely used in characterizing the repertoire of ncRNAs in organisms from all domains of life. However, the large-scale prediction and annotation of ncRNAs require multiple tools along the process, imposing a great obstacle for researchers with lesser computational or bioinformatics background. StructRNAfinder emerged as an automated tool to avoid these bottlenecks, by performing the automatic identification and complete annotation of regulatory RNA families derived directly from nucleotide sequences. In this chapter, we provide a complete tutorial for both stand-alone and web server versions of StructRNAfinder. This will help users to install the tool and to perform predictions of RNA families in any genome or transcriptome sequences dataset.

摘要

非编码RNA(ncRNA)研究在每一项基因组学或转录组学计划中已成为常规操作。根据其功能,ncRNAs可分为几个不同的RNA家族,这些家族可以由保守的一级序列、二级结构或协方差模型(CMs)来代表。CMs在预测核苷酸序列中的RNA家族方面非常敏感,并且已被广泛用于表征来自生命所有领域的生物体中的ncRNAs库。然而,ncRNAs的大规模预测和注释在整个过程中需要多个工具,这给计算或生物信息学背景较弱的研究人员带来了很大障碍。StructRNAfinder作为一种自动化工具应运而生,它通过对直接来自核苷酸序列的调控RNA家族进行自动识别和完整注释,避免了这些瓶颈。在本章中,我们为StructRNAfinder的独立版本和网络服务器版本提供了完整的教程。这将帮助用户安装该工具,并在任何基因组或转录组序列数据集中进行RNA家族的预测。

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