Symmetry in the Molecular Evolution and Genetics of Viruses and Their Interactions with Vertebrate Hosts

Dear Colleagues,

The study of viruses that infect vertebrates is furthered by the collection of large amounts of genetic sequence data and the use of advanced machine learning methods. In essence, this interaction between virus and vertebrate host is a contest between the evolution of the virus and immune defense by the host. This is particularly applicable in jawed vertebrates with their system of adaptive immunity, which includes the mechanisms of somatic recombination for an increased diversity of cellular receptors with a role in foreign peptide detection. This adaptive process in the host can lead to learning the peptide fragments of a virus, but the adaptation is challenged by the ability of a virus to continually evolve and escape from host immunity.

However, the large data collections on viruses are often sparse in their coverage of taxa and the molecular sequences of vertebrate immunity. The methods of advanced machine learning, along with related approaches, are capable of learning and creating models from sufficiently sampled and curated genetic data, even in cases of high levels of sparsity, and then for creating predictions on viral variants, the vertebrate host immune system, and the vertebrate–pathogen interactions. The deep learning methods are of particular interest because of their capability of modeling the more complex and nonlinear dynamic processes in natural systems, such as in predictive modeling involving a very large number of parameters. These approaches are also relevant for hypothesizing on the mutability of a viral type, which includes the physical constraints on its evolution and also the variation of evolutionary rates across a genome.

There is a symmetry in the evolution and genetics of viruses and the molecular-level responses by the vertebrate host. At the proximate level, each of these organisms and their populations are responding via mechanisms and processes at the genetic level, including that of mutation and recombination. This is also an information-based perspective that may be modeled with the use of a molecular evolutionary methodology and a large data sampling from populations.

The aim of this Special Issue is for the communication of knowledge on the molecular interactions between vertebrate host and viral pathogen, and it includes approaches from immunogenetics, population biology, molecular evolution, information theory, and computer science. Of particular interest are the methods of predictive modeling that relate to viral pathogens and their genomes, the emergence of new viral variants, and the molecular-level adaptations in the host immune system.

Dr. Bob Friedman
Guest Editor

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• viruses
• viral evolution
• viral genetics
• viral genomes
• viral populations
• viral variants
• viral pathogens
• immunogenetics
• adaptive immunity
• deep learning
• nonlinear dynamics
• symmetry