A non-parametric bayesian approach for predicting RNA secondary structures

Kengo Sato, Michiaki Hamada, Toutai Mituyama, Kiyoshi Asai, Yasubumi Sakakibara

研究成果: Conference contribution

1 引用 (Scopus)

抄録

Since many functional RNAs form stable secondary structures which are related to their functions, RNA secondary structure prediction is a crucial problem in bioinformatics. We propose a novel model for generating RNA secondary structures based on a non-parametric Bayesian approach, called hierarchical Dirichlet processes for stochastic context-free grammars (HDP-SCFGs). Here non-parametric means that some meta-parameters, such as the number of non-terminal symbols and production rules, do not have to be fixed. Instead their distributions are inferred in order to be adapted (in the Bayesian sense) to the training sequences provided. The results of our RNA secondary structure predictions show that HDP-SCFGs are more accurate than the MFE-based and other generative models.

元の言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ページ286-297
ページ数12
5724 LNBI
DOI
出版物ステータスPublished - 2009
外部発表Yes
イベント9th International Workshop on Algorithms in Bioinformatics, WABI 2009 - Philadelphia, PA
継続期間: 2009 9 122009 9 13

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
5724 LNBI
ISSN(印刷物)03029743
ISSN(電子版)16113349

Other

Other9th International Workshop on Algorithms in Bioinformatics, WABI 2009
Philadelphia, PA
期間09/9/1209/9/13

Fingerprint

RNA Secondary Structure
RNA
Bayesian Approach
Dirichlet Process
Structure Prediction
Context-free Grammar
Context free grammars
Production Rules
Generative Models
Secondary Structure
Bioinformatics
Model

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

これを引用

Sato, K., Hamada, M., Mituyama, T., Asai, K., & Sakakibara, Y. (2009). A non-parametric bayesian approach for predicting RNA secondary structures. : Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (巻 5724 LNBI, pp. 286-297). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 5724 LNBI). https://doi.org/10.1007/978-3-642-04241-6_24

A non-parametric bayesian approach for predicting RNA secondary structures. / Sato, Kengo; Hamada, Michiaki; Mituyama, Toutai; Asai, Kiyoshi; Sakakibara, Yasubumi.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 巻 5724 LNBI 2009. p. 286-297 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻 5724 LNBI).

研究成果: Conference contribution

Sato, K, Hamada, M, Mituyama, T, Asai, K & Sakakibara, Y 2009, A non-parametric bayesian approach for predicting RNA secondary structures. : Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 巻. 5724 LNBI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 巻. 5724 LNBI, pp. 286-297, 9th International Workshop on Algorithms in Bioinformatics, WABI 2009, Philadelphia, PA, 09/9/12. https://doi.org/10.1007/978-3-642-04241-6_24
Sato K, Hamada M, Mituyama T, Asai K, Sakakibara Y. A non-parametric bayesian approach for predicting RNA secondary structures. : Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 巻 5724 LNBI. 2009. p. 286-297. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-04241-6_24
Sato, Kengo ; Hamada, Michiaki ; Mituyama, Toutai ; Asai, Kiyoshi ; Sakakibara, Yasubumi. / A non-parametric bayesian approach for predicting RNA secondary structures. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 巻 5724 LNBI 2009. pp. 286-297 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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