Abstract
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.
Original language | English (US) |
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Pages (from-to) | 295-310 |
Number of pages | 16 |
Journal | Match |
Volume | 80 |
Issue number | 2 |
State | Published - 2018 |
Bibliographical note
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