To predict RNA structures with pseudoknots, traditional stochastic grammar models must collect several related labeled RNA sequences, which limits the practical application of this method. In order to use a large number of unlabeled RNA sequences effectively for structure prediction, the combination of stochastic grammar and semi-supervised learning techniques has been proposed. In these techniques, we used a small amount of labeled RNA sequences and a large number of unlabeled sequences as a training set of the prediction model. Designing a se...
