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

Damian Panas, Piotr Waz, Dorota Bielinska-Waz, Ashesh Nandy, Subhash C. Basak

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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 languageEnglish (US)
Pages (from-to)295-310
Number of pages16
JournalMatch
Volume80
Issue number2
StatePublished - Jan 1 2018

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