RIblast: an ultrafast RNA-RNA interaction prediction system based on a seed-and-extension approach

研究成果: Article査読

40 被引用数 (Scopus)


Motivation: 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.

Results: 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.

Availability and implementation: The source code of RIblast is freely available at https://github.com/fukunagatsu/RIblast .

Contact: t.fukunaga@kurenai.waseda.jp or mhamada@waseda.jp.

Supplementary information: Supplementary data are available at Bioinformatics online.

ジャーナルBioinformatics (Oxford, England)
出版ステータスPublished - 2017 9月 1

ASJC Scopus subject areas

  • 統計学および確率
  • 生化学
  • 分子生物学
  • コンピュータ サイエンスの応用
  • 計算理論と計算数学
  • 計算数学


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