Open AccessRecognition of Herpes Viruses on the Basis of a New Metric for Protein Sequences
Author(s) -
Valentina Sulimova,
Oleg Seredin,
Vadim Mottl
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1368/5/052039
Subject(s) - metric (unit) , measure (data warehouse) , similarity (geometry) , basis (linear algebra) , sequence (biology) , similarity measure , pattern recognition (psychology) , scheme (mathematics) , artificial intelligence , computer science , contrast (vision) , quality (philosophy) , mathematics , computational biology , data mining , biology , image (mathematics) , genetics , physics , engineering , mathematical analysis , operations management , geometry , quantum mechanics
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.