Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
531419 | Pattern Recognition | 2009 | 8 Pages |
Abstract
Much attention has been paid to RNA–RNA interaction involved in posttranscriptional regulation of gene expression. Although there have been a few studies on secondary structure prediction of interacting RNAs using dynamic programming (DP) algorithms, no grammar-based approach has been proposed. This paper provides a new modeling for RNA–RNA interaction based on multiple context-free grammar (MCFG). We present a polynomial time parsing (prediction) algorithm of the stochastic version of MCFG. Experimental results show that our approach is comparable to an existing work based on DP. The MCFG-based approach is more flexible than other DP-based methods.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Yuki Kato, Tatsuya Akutsu, Hiroyuki Seki,