An application of the 2D-dynamic representation of DNA/RNA sequences to the prediction of influenza a virus subtypes

A new theoretical method for the virus identifcation has been proposed. The 2D-Dynamic Representation of DNA/RNA Sequences has been applied to the prediction of influenza A virus subtypes. We have shown that the method can be successfully combined with novel supervised machine learning algorithms, such as C5.0. The descriptors of the 2D-Dynamic Representation of DNA/RNA Sequences have been evaluated. High mean accuracy of predicting the subtype of the influenza A virus has been obtained (over 90% of correct predictions). As a consequence, the combination of the machine learning algorithms and the 2D-Dynamic Representation of DNA/RNA Sequences has been shown to constitute a simple and accurate tool for the classifcation of unidentifed virus strains.