R2DT is a framework for predicting and visualising RNA secondary structure using templates.
R2DT is a framework for predicting and visualising RNA secondary structure using templates.
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DOI：
10.1038/s41467-021-23555-5
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发表时间：
2021-06-09
影响因子：
16.6
通讯作者：
Petrov AI
中科院分区：
文献类型：
--
作者：
Sweeney BA;Hoksza D;Nawrocki EP;Ribas CE;Madeira F;Cannone JJ;Gutell R;Maddala A;Meade CD;Williams LD;Petrov AS;Chan PP;Lowe TM;Finn RD;Petrov AI
非编码RNA（NCRNA）对于所有生命都是必不可少的，它们的功能通常取决于其次要（2D）和三级结构，尽管有大量的NCRNA可视化软件，很少有自动产生一致的人物它挑战用户在这里构建，比较和分析结构。 R2DT是基于代表大多数已知结构化RNA的3,647个模板的库。可以在https://github.com/rnacentral/r2dt上免费获得社区扩展，并在https://rnacentral.org/r2dt上找到Web服务器。
非编码RNA功能的理解很差，部分是由于在这里确定RNA次级（2D）结构的挑战。功能的RNA序列。
Non-coding RNAs (ncRNA) are essential for all life, and their functions often depend on their secondary (2D) and tertiary structure. Despite the abundance of software for the visualisation of ncRNAs, few automatically generate consistent and recognisable 2D layouts, which makes it challenging for users to construct, compare and analyse structures. Here, we present R2DT, a method for predicting and visualising a wide range of RNA structures in standardised layouts. R2DT is based on a library of 3,647 templates representing the majority of known structured RNAs. R2DT has been applied to ncRNA sequences from the RNAcentral database and produced >13 million diagrams, creating the world’s largest RNA 2D structure dataset. The software is amenable to community expansion, and is freely available at https://github.com/rnacentral/R2DT and a web server is found at https://rnacentral.org/r2dt. Non-coding RNA function is poorly understood, partly due to the challenge of determining RNA secondary (2D) structure. Here, the authors present a framework for the reproducible prediction and visualization of the 2D structure of a wide array of RNAs, which enables linking RNA sequence to function.
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DOI：
10.1093/bioinformatics/btp250
发表时间：
2009-08-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Darty K;Denise A;Ponty Y
通讯作者：
Ponty Y
影响因子：
10.7
作者：
Bernier, Chad R.;Petrov, Anton S.;Williams, Loren Dean
通讯作者：
Williams, Loren Dean
影响因子：
6.8
作者：
Gutell, RR;Lee, JC;Cannone, JJ
通讯作者：
Cannone, JJ
影响因子：
3
作者：
Elias R;Hoksza D
通讯作者：
Hoksza D
影响因子：
14.9
作者：
BRENNAN, T;SUNDARALINGAM, M
通讯作者：
SUNDARALINGAM, M