Much attention has been paid to two interacting RNA molecules involved in post‐transcriptional control of gene expression. Although there have been a few studies on RNA‐RNA interaction prediction based on dynamic programming algorithm, no grammar‐based approach has been proposed. The purpose of this paper is to provide a new modeling for RNA‐RNA interaction based on multiple context‐free grammar (MCFG). We present a polynomial time parsing algorithm for finding the most likely derivation tree for the stochastic version of MCFG, which is applicable to RNA joint secondary structure prediction including kissing hairpin loops. Also, elementary tests on RNA‐RNA interaction prediction have shown that the proposed method is comparable to Alkan et al.'s method.
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2 November 2007
COMPUTATIONAL MODELS FOR LIFE SCIENCES—CMLS '07: 2007 International Symposium on Computational Models of Life Sciences
17–19 December 2007
Gold Coast, Queensland (Australia)
Research Article|
November 02 2007
A Grammatical Approach to RNA‐RNA Interaction Prediction
Yuki Kato;
Yuki Kato
aBioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611‐0011, Japan
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Tatsuya Akutsu;
Tatsuya Akutsu
aBioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611‐0011, Japan
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Hiroyuki Seki
Hiroyuki Seki
bGraduate School of Information Science, Nara Institute of Science and Technology, 8916‐5 Takayama, Ikoma, Nara 630‐0192, Japan
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AIP Conf. Proc. 952, 197–206 (2007)
Citation
Yuki Kato, Tatsuya Akutsu, Hiroyuki Seki; A Grammatical Approach to RNA‐RNA Interaction Prediction. AIP Conf. Proc. 2 November 2007; 952 (1): 197–206. https://doi.org/10.1063/1.2816623
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