Fu X Z, Wang H, Harrison R W, Harrison W L
Department of Computer Science, Georgia State University, Atlanta, GA 30303, USA.
Int J Data Min Bioinform. 2008;2(1):78-93. doi: 10.1504/ijdmb.2008.016757.
RNA plays a critical role in mediating every step of cellular information transfer from genes to functional proteins. Pseudoknots are functionally important and widely occurring structural motifs found in all types of RNA. Therefore predicting their structures is an important problem. In this paper, we present a new RNA pseudoknot structure prediction method based on term rewriting. The method is implemented using the Mfold RNA/DNA folding package and the term rewriting language Maude. In our method, RNA structures are treated as terms and rules are discovered for predicting pseudoknots. Our method 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 ranging from prediction of pseudoknots to discovery of higher level RNA structures involving complex RNA tertiary interactions.
RNA在介导细胞信息从基因到功能性蛋白质传递的每一步过程中都起着关键作用。假结是在所有类型的RNA中发现的功能重要且广泛存在的结构基序。因此，预测它们的结构是一个重要问题。在本文中，我们提出了一种基于项重写的新的RNA假结结构预测方法。该方法使用Mfold RNA/DNA折叠软件包和项重写语言Maude来实现。在我们的方法中，RNA结构被视为项，并发现用于预测假结的规则。我们的方法在PseudoBase中的211个假结上进行了测试，与实验确定的结构相比，平均准确率达到74.085%。事实上，我们的方法发现的大多数假结准确率都在90%以上。这些结果表明，项重写在RNA应用中具有广泛的潜力，从假结预测到涉及复杂RNA三级相互作用的更高级RNA结构的发现。
