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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.
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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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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