RIblast: an ultrafast RNA-RNA interaction prediction system based on a seed-and-extension approach.
RIblast: an ultrafast RNA-RNA interaction prediction system based on a seed-and-extension approach.
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DOI：
10.1093/bioinformatics/btx287
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发表时间：
2017-09-01
期刊：
影响因子：
--
通讯作者：
Hamada M
中科院分区：
文献类型：
--
作者：
Fukunaga T;Hamada M
lncRNA在多种生物过程中发挥重要作用。尽管人类已发现了超过58000个lncRNA基因，但大多数已知的lncRNA仍缺乏表征。理解lncRNA功能的一种方法是检测每个lncRNA的相互作用RNA靶标。由于lncRNA-RNA相互作用的实验检测是困难的，lncRNA-RNA相互作用的计算预测是不可或缺的技术。然而，现有的RNA-RNA相互作用预测工具的高计算成本阻碍了它们在大规模lncRNA数据集上的应用。在这里，我们提出了“RIblast”，一个超快的RNA-RNA相互作用预测方法的基础上的种子和延伸的方法。RIblast使用后缀阵列发现种子区域，并随后基于RNA二级结构能量模型扩展种子区域。计算实验表明，RIblast达到了与现有程序相似的预测精度水平，但速度比现有程序快64倍以上。RIblast的源代码可以在https://github.com/fukunagatsu/RIblast上免费获得。 补充数据可在Bioinformatics在线获得。
LncRNAs play important roles in various biological processes. Although more than 58 000 human lncRNA genes have been discovered, most known lncRNAs are still poorly characterized. One approach to understanding the functions of lncRNAs is the detection of the interacting RNA target of each lncRNA. Because experimental detections of comprehensive lncRNA–RNA interactions are difficult, computational prediction of lncRNA–RNA interactions is an indispensable technique. However, the high computational costs of existing RNA–RNA interaction prediction tools prevent their application to large-scale lncRNA datasets. Here, we present ‘RIblast’, an ultrafast RNA–RNA interaction prediction method based on the seed-and-extension approach. RIblast discovers seed regions using suffix arrays and subsequently extends seed regions based on an RNA secondary structure energy model. Computational experiments indicate that RIblast achieves a level of prediction accuracy similar to those of existing programs, but at speeds over 64 times faster than existing programs. The source code of RIblast is freely available at https://github.com/fukunagatsu/RIblast. Supplementary data are available at Bioinformatics online.
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