RNA plays a critical role in mediating every step of cellular information transfer from genes to functional proteins. Pseudoknots are widely occurring structural motifs found in all types of RNA and are also functionally important. Therefore predicting their structures is an important problem. In this paper, we present a new RNA pseudoknot prediction model based on term rewriting rather than on dynamic programming, comparative sequence analysis, or context-free grammars. The model we describe is implemented using the Mfold RNA/DNA folding package and the term rewriting language Maude. Our model was tested on 211 pseudoknots in PseudoBase and achieves an average accuracy of 74.085% compared to the experimentally determined structure. In fact, most pseudoknots discovered by our method achieve an accuracy of above 90%. These results indicate that term rewriting has a broad potential in RNA applications from prediction of pseudoknots to higher level RNA structures involving complex RNA te...
Xuezheng Fu, Hao Wang, William L. Harrison, Robert