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探索用于长链非编码RNA分析的工具和资源全景。

Exploring the landscape of tools and resources for the analysis of long non-coding RNAs.

作者信息

Ballarino Monica, Pepe Gerardo, Helmer-Citterich Manuela, Palma Alessandro

机构信息

Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Piazzale Aldo Moro 5, 00161 Rome, Italy.

Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 1, 00133 Rome, Italy.

出版信息

Comput Struct Biotechnol J. 2023 Sep 29;21:4706-4716. doi: 10.1016/j.csbj.2023.09.041. eCollection 2023.

Abstract

In recent years, research on long non-coding RNAs (lncRNAs) has gained considerable attention due to the increasing number of newly identified transcripts. Several characteristics make their functional evaluation challenging, which called for the urgent need to combine molecular biology with other disciplines, including bioinformatics. Indeed, the recent development of computational pipelines and resources has greatly facilitated both the discovery and the mechanisms of action of lncRNAs. In this review, we present a curated collection of the most recent computational resources, which have been categorized into distinct groups: databases and annotation, identification and classification, interaction prediction, and structure prediction. As the repertoire of lncRNAs and their analysis tools continues to expand over the years, standardizing the computational pipelines and improving the existing annotation of lncRNAs will be crucial to facilitate functional genomics studies.

摘要

近年来,由于新发现的转录本数量不断增加,对长链非编码RNA(lncRNA)的研究受到了广泛关注。lncRNA的几个特性使其功能评估具有挑战性,这就迫切需要将分子生物学与包括生物信息学在内的其他学科相结合。事实上,计算流程和资源的最新发展极大地促进了lncRNA的发现及其作用机制的研究。在本综述中,我们精心收集了最新的计算资源,并将其分为不同的类别:数据库与注释、识别与分类、相互作用预测和结构预测。随着lncRNA及其分析工具的种类在多年来不断扩展,规范计算流程并改进lncRNA的现有注释对于促进功能基因组学研究至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1114/10568309/668a3ee98042/ga1.jpg

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