A study of permutation crossover operators on the traveling salesman problem
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Pseudoknots in RNA secondary structures
RECOMB '00 Proceedings of the fourth annual international conference on Computational molecular biology
AllelesLociand the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
CBMS '06 Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems
RnaPredict—An Evolutionary Algorithm for RNA Secondary Structure Prediction
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Linear time algorithm for parsing RNA secondary structure
WABI'05 Proceedings of the 5th International conference on Algorithms in Bioinformatics
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Beyond its critical role in protein synthesis, RNA has vital structural, functional, and regulatory roles in the cell. The shape of an RNA molecule primarily determines its function in organic systems, so there is notable interest in the computational prediction of RNA structure. Pseudoknots are relatively rare but important structural elements which are difficult to predict computationally. RnaPredict is an evolutionary algorithm (EA) developed for the prediction of RNA secondary structure. This research evaluates RnaPredict after its enhancement with the thermodynamic model from HotKnots, a model specifically designed to compute free energies of structures containing pseudoknots. The performance of the EA is evaluated against the original HotKnots algorithm. RnaPredict significantly improved upon the sensitivity and specificity of structures predicted by HotKnots.