RnaPredict—An Evolutionary Algorithm for RNA Secondary Structure Prediction

Abstract

This paper presents two in-depth studies on RnaPredict, an evolutionary algorithm for RNA secondary structure prediction. The first study is an analysis of the performance of two thermodynamic models, Individual Nearest Neighbor (INN) and Individual Nearest Neighbor Hydrogen Bond (INN-HB). The correlation between the free energy of predicted structures and the sensitivity is analyzed for 19 RNA sequences. Although some variance is shown, there is a clear trend between a lower free energy and an increase in true positive base pairs. With increasing sequence length, this correlation generally decreases. In the second experiment, the accuracy of the predicted structures for these 19 sequences are compared against the accuracy of the structures generated by the mfold dynamic programming algorithm (DPA) and also to known structures. RnaPredict is shown to outperform the minimum free energy structures produced by mfold and has comparable performance when compared to sub-optimal structures produced by mfold.

Particle swarm optimization for finding RNA secondary structures

“…We compare our results to those of RnaPredict in [42], where the best values obtained for 30 random seeds and 12 operator combinations are listed. Results for SARNA-Predict are taken from [35,36], where 100 runs were executed for various parameter combinations on each test sequence.…”

“…Massively parallel implementations [31] as well as efficient algorithms for small architectures exist [34]. RnaPredict and its parallelized version P-RnaPredict are GAs for predicting RNA secondary structure that have evolved to levels of prediction quality comparable to mfold ( [44,42]). Recently, the Simulated Annealing algorithm SARNA-Predict has been introduced ( [35,36]).…”

“…A preliminary version of HelixPSO that was used only for finding secondary structures with low free energy was described in [20]. The optimization behavior of HelixPSO is compared to the algorithms RnaPredict ( [44,42]), SARNA-Predict ( [35,36]), and SetPSO ( [24]) on standard sets of RNA test molecules. A parallel version of HelixPSO is also proposed in this paper and it is shown that is efficient for small and medium size PC Clusters.…”

pEvoSAT

“…Unlike classical GA based methods, permutation based GAs seek to represent individuals as an ordered set of elements relating to the problem [17,16,19,13,18]. The classical representation of SAT individuals, as mentioned in Section 1.3, is a string of length n of 0s and 1s that corresponds to an assignment of the n variables.…”

HSRNAFold: A harmony search algorithm for RNA secondary structure prediction based on minimum free energy

“…The more recent GAs works in this area are RnaPredict and its parallelized version PRnaPredict which proposed by Wiese and his students. They showed that the quality of their algorithm is comparable to Mfold [12,13]. SARNA-Predict is a SA algorithm has been introduced in [3,14] which has used to predict RNA secondary structure that has a low free energy and a high number of correctly predicted base pairs when compared to the known native structures.…”