We propose applying t-distributed stochastic neighbor embedding to protein sequences of SARS-CoV-2 to construct, visualize and study the evolutionary space of the coronavirus. The basic idea is to explore the COVID-19 evolution space by using modern manifold learning techniques applied to evolutionary distances between variants. Evolutionary distances have been calculated based on the structures of the nucleocapsid and spike proteins.
Authors
- Dr. Gaik Tamazian,
- Dr. Andrey Komissarov,
- Dr. Dmitry Kobak,
- Dr. Dmitry Polyakov,
- Dr. Evegeny Andronov,
- Prof Sergei Nechaev,
- dr hab. Sergey Kryzhevich link open in new tab ,
- Dr. Yuri Porozov,
- Prof. Eugene Stepanov
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1007/978-3-031-23198-8_23
- Category
- Publikacja monograficzna
- Type
- rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
- Language
- angielski
- Publication year
- 2022
