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t-SNE Highlights Phylogenetic and Temporal Patterns of SARS-CoV-2 Spike and Nucleocapsid Protein Evolution
Abstract
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.
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Authors (9)
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Gaik Tamazian Dr.
- Peter the Great Saint Petersburg Polytechnic University
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Andrey Komissarov Dr.
- Smorodintsev Research Institute of Influenza, St. Petersburg
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Dmitry Kobak Dr.
- University of Tübingen, Tübingen, Germany
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Dmitry Polyakov Dr.
- Higher School of Economics
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Evegeny Andronov Dr.
- All-Russia Research Institute for Agricultural Microbiology, Russian Academy of Sciences
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Sergei Nechaev Prof
- LPTMS, Universitè Paris Saclay
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Yuri Porozov Dr.
- The Center of Bio- and Chemoinformatics, I.M. Sechenov First Moscow State Medical University
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Eugene Stepanov Prof.
- Scuola Normale Superiore, Pisa
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Keywords
Details
- Category:
- Monographic publication
- Type:
- rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
- Language:
- English
- Publication year:
- 2022
- Bibliographic description:
- Tamazian G., Komissarov A., Kobak D., Polyakov D., Andronov E., Nechaev S., Kryzhevich S., Porozov Y., Stepanov E.: t-SNE Highlights Phylogenetic and Temporal Patterns of SARS-CoV-2 Spike and Nucleocapsid Protein Evolution// / : , 2023,
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/978-3-031-23198-8_23
- Sources of funding:
-
- Free publication
- Verified by:
- Gdańsk University of Technology
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