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Acta Naturae. 2017 Jul-Sep;9(3):48-54.
Predicting the Evolutionary Variability of the Influenza A Virus.
Timofeeva TA1, Asatryan MN1, Altstein AD1, Narodisky BS1, Gintsburg AL1, Kaverin NV1.
Author information
Abstract
The influenza A virus remains one of the most common and dangerous human health concerns due to its rapid evolutionary dynamics. Since the evolutionary changes of influenza A viruses can be traced in real time, the last decade has seen a surge in research on influenza A viruses due to an increase in experimental data (selection of escape mutants followed by examination of their phenotypic characteristics and generation of viruses with desired mutations using reverse genetics). Moreover, the advances in our understanding are also attributable to the development of new computational methods based on a phylogenetic analysis of influenza virus strains and mathematical (integro-differential equations, statistical methods, probability-theory-based methods) and simulation modeling. Continuously evolving highly pathogenic influenza A viruses are a serious health concern which necessitates a coupling of theoretical and experimental approaches to predict the evolutionary trends of the influenza A virus, with a focus on the H5 subtype.
KEYWORDS:
Influenza A virus; computational modeling; computational tools; escape mutants; phenotypic characteristics; phylogenetic trees; reverse genetics
PMID: 29104775
Predicting the Evolutionary Variability of the Influenza A Virus.
Timofeeva TA1, Asatryan MN1, Altstein AD1, Narodisky BS1, Gintsburg AL1, Kaverin NV1.
Author information
Abstract
The influenza A virus remains one of the most common and dangerous human health concerns due to its rapid evolutionary dynamics. Since the evolutionary changes of influenza A viruses can be traced in real time, the last decade has seen a surge in research on influenza A viruses due to an increase in experimental data (selection of escape mutants followed by examination of their phenotypic characteristics and generation of viruses with desired mutations using reverse genetics). Moreover, the advances in our understanding are also attributable to the development of new computational methods based on a phylogenetic analysis of influenza virus strains and mathematical (integro-differential equations, statistical methods, probability-theory-based methods) and simulation modeling. Continuously evolving highly pathogenic influenza A viruses are a serious health concern which necessitates a coupling of theoretical and experimental approaches to predict the evolutionary trends of the influenza A virus, with a focus on the H5 subtype.
KEYWORDS:
Influenza A virus; computational modeling; computational tools; escape mutants; phenotypic characteristics; phylogenetic trees; reverse genetics
PMID: 29104775