Secondary structure element voting for RNA gene finding

An exploration of the use of multiple secondary structure elements for structural RNA gene finding is conducted. The secondary structure models are combined through a multilayer voting system which first combines the probability output of support vector machines and then combines the results of those votes to predict whether a sequence is a structural RNA gene or not. It is found that the voting in the first layer of the system has significant impact on the performance of individual secondary structure element models with improvements in classification results of up to 56%. Likewise, gains in classification F-measure over 0.6 were seen when two secondary structure element model predictions were voted together. When all the secondary structure element models were used in voting, an accuracy of over 93% was achieved by the secondary structure RNA gene classification system.