Recognition of Herpes Viruses on the Basis of a New Metric for Protein Sequences

This paper addresses the problem of intellectual human herpes viruses recognition based on the analysis of their protein sequences. To compare proteins, we use a new dissimilarity measure based on finding an optimal sequence alignment. In the previous work, we proved that the proposed way of sequence comparison generates a measure that has properties of a metric. These properties allow for more convenient and effective use of the proposed measure in further analysis in contrast to the traditional similarity measure, such as Needleman-Wunch alignment. The results of herpes viruses recognition show, that the metric properties allow to improve the classification quality. In addition, in this paper, we adduce an updated computational scheme for the proposed metric, which allows to speed up the comparison of proteins.

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