PATTERNA: transcriptome-wide search for functional RNA elements via structural data signatures.

PATTERNA: transcriptome-wide search for functional RNA elements via structural data signatures.
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DOI:
10.1186/s13059-018-1399-z
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发表时间:
2018-03-01
期刊:
影响因子:
12.3
通讯作者:
Aviran S
Aviran S
中科院分区:
生物学1区
文献类型:
--
作者:
Ledda M;Aviran S

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建立RNA结构和功能之间的联系仍然是RNA生物学的一大挑战。高通量结构分析实验的出现正在彻底改变我们破译结构的能力,但直接从这些数据集中提取结构元素信息的原则方法尚缺乏。我们提出了patteRNA,一种无监督模式识别算法,可以从分析数据中快速挖掘RNA结构基序。我们证明了patteRNA以与常用热力学模型相当的精度检测基序,并强调了它在从大数据集自动化数据导向结构建模中的实用性。patteRNA是通用的,与不同的分析技术和实验条件兼容。本文的在线版本(10.1186/s13059-018-1399-z)包含补充内容,仅供授权用户使用。
Establishing a link between RNA structure and function remains a great challenge in RNA biology. The emergence of high-throughput structure profiling experiments is revolutionizing our ability to decipher structure, yet principled approaches for extracting information on structural elements directly from these data sets are lacking. We present patteRNA, an unsupervised pattern recognition algorithm that rapidly mines RNA structure motifs from profiling data. We demonstrate that patteRNA detects motifs with an accuracy comparable to commonly used thermodynamic models and highlight its utility in automating data-directed structure modeling from large data sets. patteRNA is versatile and compatible with diverse profiling techniques and experimental conditions. The online version of this article (10.1186/s13059-018-1399-z) contains supplementary material, which is available to authorized users.
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