RNA-RNA interaction prediction using hybrid optimization

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In this work, we developed a novel method for RNA joint secondary structure prediction that aims at RNA. RNA interaction prediction by integrating the maximizing expected accuracy principle with integer programming. Furthermore, based on the idea of the proposed method, we presented an algorithm for predicting RNA secondary structures with pseudoknots, a class of complex substructures, when a single RNA sequence is given. Experimental results on real data sets indicate that both methods are at least comparable in prediction accuracy to existing methods, and even more importantly, are overwhelmingly faster than the early predictors. A web server that implements the proposed methods is free and open to all users.