Algorithms for Processing Coronavirus Genomes for the Goals and Objectives of Modern Immunoinformatics, Vaccinomics, and Virology

Abstract

The novel coronavirus pandemic has stimulated the scientific activity of virology and interdisciplinary sciences: medical cybernetics and bioinformatics. The article is focused on the study of algorithms for processing bioinformatic data of genomic origin predominantly for the purposes of predominantly immunoinformatics and computational vaccinology. The schemes of algorithms developed by the authors for the analysis of bioinformatic data are presented. The algorithms for processing genomic information developed by the authors based on the analysis of the available literature and many years of experience in computational and laboratory experiments can be used not only for the design and analysis of epitope vaccine components, but also for the other tasks of computational virology and microbiology. In silico experiments on the analysis of bioinformatic data are relatively low-cost and multi-informative, but they require highly qualified scientists with extensive experience, interdisciplinary training, and, accordingly, a wide range of knowledge and skills. However, for the complete analysis and implementation of, for example, the epitope vaccines, subsequent validation by the laboratory and in vivo experiments are required.

Keywords

• sars-cov-2
• covid-19
• coronavirus
• epidemic
• pandemic
• automated data processing systems
• software
• medical cybernetics
• genomics
• transcriptomics
• medical systems
• immunoinformatics