RNA inverse folding using Monte Carlo tree search

Xiufeng Yang, Kazuki Yoshizoe, Akito Taneda, Koji Tsuda

研究成果: ジャーナルへの寄稿学術誌査読

4 被引用数 (Scopus)

抄録

Background: Artificially synthesized RNA molecules provide important ways for creating a variety of novel functional molecules. State-of-the-art RNA inverse folding algorithms can design simple and short RNA sequences of specific GC content, that fold into the target RNA structure. However, their performance is not satisfactory in complicated cases. Result: We present a new inverse folding algorithm called MCTS-RNA, which uses Monte Carlo tree search (MCTS), a technique that has shown exceptional performance in Computer Go recently, to represent and discover the essential part of the sequence space. To obtain high accuracy, initial sequences generated by MCTS are further improved by a series of local updates. Our algorithm has an ability to control the GC content precisely and can deal with pseudoknot structures. Using common benchmark datasets for evaluation, MCTS-RNA showed a lot of promise as a standard method of RNA inverse folding. Conclusion: MCTS-RNA is available at https://github.com/tsudalab/MCTS-RNA.

本文言語英語
論文番号468
ジャーナルBMC bioinformatics
18
1
DOI
出版ステータス出版済み - 11月 6 2017
外部発表はい

!!!All Science Journal Classification (ASJC) codes

  • 構造生物学
  • 生化学
  • 分子生物学
  • コンピュータ サイエンスの応用
  • 応用数学

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