Computational predictors of the predominant protein function: SARS-CoV-2 case
Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms
; : 47-61, 2022.
Artigo
em Inglês
| Scopus | ID: covidwho-2276678
ABSTRACT
In this chapter, we describe the main molecular features of SARS-CoV-2 that cause COVID-19 disease, as well as a high-efficiency computational prediction called Polarity Index Method®. We also introduce a molecular classification of the RNA virus and DNA virus families and two main classifications supervised and non-supervised algorithms of the predictions of the predominant function of proteins. Finally, some results obtained by the proposed non-supervised method are given, as well as some particularities found about the linear representation of proteins. © 2022 Scrivener Publishing LLC.
Texto completo:
Disponível
Coleções:
Bases de dados de organismos internacionais
Base de dados:
Scopus
Tipo de estudo:
Estudo prognóstico
Idioma:
Inglês
Revista:
Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms
Ano de publicação:
2022
Tipo de documento:
Artigo
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